Platforms and systems for automated cell culture

ABSTRACT

Disclosed herein are platforms, systems, and methods including a cell culture system that includes a cell culture container comprising a cell culture, the cell culture receiving input cells, a cell imaging subsystem configured to acquire images of the cell culture, a computing subsystem configured to perform a cell culture process on the cell culture according to the images acquired by the cell imaging subsystem, and a cell editing subsystem configured to edit the cell culture to produce output cell products according to the cell culture process.

CROSS-REFERENCE

This application claims the benefit of U.S. Provisional Application No.63/216,558, filed Jun. 30, 2021, U.S. Provisional Application No.63/249,698, filed Sep. 29, 2021, U.S. Provisional Application No.63/288,859, filed Dec. 13, 2021, U.S. Provisional Application No.63/167,114, filed Mar. 28, 2021, U.S. Provisional Application No.63/222,059, filed Jul. 15, 2021, U.S. Provisional Application No.63/239,995, filed Sep. 2, 2021, U.S. Provisional Application No.63/282,351, filed Nov. 23, 2021, U.S. Provisional Application No.63/295,968, filed Jan. 3, 2022, U.S. Provisional Application No.63/298,241, filed Jan. 11, 2022, U.S. Provisional Application No.63/210,243, filed Jun. 14, 2021, U.S. Provisional Application No.63/157,731, filed Mar. 7, 2021, U.S. Provisional Application No.63/297,290, filed Jan. 7, 2022, U.S. Provisional Application No.63/194,306, filed May 28, 2021, U.S. Provisional Application No.63/284,839, filed Dec. 1, 2021, U.S. Provisional Application No.63/226,128, filed Jul. 27, 2021, U.S. Provisional Application No.63/311,673, filed Feb. 18, 2022, and U.S. Provisional Application No.63/196,904, filed Jun. 4, 2021, which are hereby incorporated byreference in their entirety herein.

INCORPORATION BY REFERENCE

All publications, patents, and patent applications mentioned in thisspecification are herein incorporated by reference to the same extent asif each individual publication, patent, or patent application wasspecifically and individually indicated to be incorporated by reference.

BACKGROUND

The stochastic nature of cell processes has long plagued biologicalmanufacturing efforts. This has been particularly true of processes inmammalian cells that involve phenotype transitions, for example inducedpluripotent stem cell (iPSC) reprogramming or stem cell differentiationinto targets cells or trans-differentiation. Additionally, processesincluding gene editing, which may be combined with the above processes,add yet more process variability. Finally, patient-specific processes,such as those for autologous cell therapies or patient-specific drugdiscovery, are notoriously unpredictable. As a result, many cellprocesses are so variable, low-yielding, and/or labor intensive thatthey do not reach the clinic. Even if they do, the low yields, laborrequirements, required purification and sorting steps, and multipletransfers between cell culture containers make the process extremelyexpensive and unscalable to a large patient population.

One current approach for large scale biological manufacturing involvesthe use of large bioreactors, such as stirred bioreactors, in whichcells are cultured in suspension, often in clumps/aggregates or onmicrocarriers. However, yields from such bulk processes are typicallyinefficient, manually managed 2-dimensional cell culture vessels. Theadvantage of the bioreactor approach is sheer volume of cells, but theprocess has virtually no feedback control to account for lot-to-lot,patient-to-patient or clone-to-clone variability. Filtration steps maybe added to refine the cell product, but these often reduce theviability or functionality of the cell product and can have enormousyield impacts. A deviation in cell behavior early in the process maycause catastrophically low yield or performance on quality control (QC)assays and is almost never detectable until the end of the process.

The manual approach in 2D cell culture vessels seeks to address thisvariability by adding a highly-trained operator or scientist to makeobservations and “edits” to the cell culture. Most often these editstake the form of selective transfer from one culture container/vessel toanother, repeated on a regular basis as the cell culture grows tomaximum density, often due to the growth of undesirable cells alongsidethe target cells. While this manual process can eliminate grossdeviations in the cell culture process, the subjective decision making(often based on single timepoint views through a dissection microscope),manual mechanical manipulation of cells and colonies, and frequenttransfer between cell culture containers make this process expensive,unscalable, and prone to a high degree of variability and subject tocontamination unless performed in dedicated, expensive, high-gradecleanroom facilities. Automation would solve some of these issues, butobjective evaluation of the quality of cell cultures during the cellculture process is lacking. Thus a fast, accurate, automated, andscalable system for biological manufacturing is needed.

SUMMARY

Disclosed herein are platforms, systems, and methods for biologicalmanufacturing. Various implementations of the present disclosure providedistinct advantages over the conventional cell culture process such asautomated cell culture for more efficient manufacturing, enhancedcell/colony imaging techniques for detection of cell quality featureswithout invasive labeling, machine learning image analysis for objectivedetermination of cell product quality, closed-environment cell culturesystems allowing end-to-end sterile manufacturing, improved cell cultureediting for selection of high quality cell products, andscalable/modular cell culture systems for more efficient manufacturing.Components and subsystems of the overall platform or system can beimplemented individually or in any combination to achieve one or more ofthese advantages.

Disclosed herein are platforms, systems, and methods including a cellculture system that includes a cell culture container comprising a cellculture, the cell culture receiving input cells, a cell imagingsubsystem configured to acquire images of the cell culture, a computingsubsystem configured to perform a cell culture process on the cellculture according to the images acquired by the cell imaging subsystem,and a cell editing subsystem configured to edit the cell culture toproduce output cell products according to the cell culture process. Thesubsystems disclosed herein can function as independent systems thatprovide technical improvements over the conventional cell cultureprocess without requiring the other subsystems. Alternatively, one ormore combinations of the subsystems can be integrated within an overallplatform or cell culture system to achieve greater synergy in providinga fast, accurate, automated, and scalable system for biologicalmanufacturing.

Disclosed herein are platforms, systems, and methods for automated cellculture. The automated cell culture can be carried out by a cell culturesystem comprising a cell culture container comprising a cell culture(e.g., a cell culture chamber comprising one or more adherent orsemi-adherent cells), the cell culture configured to receive inputcells. The cell culture system can be include a cell imaging subsystemconfigured to acquire images of the cell culture. The cell culturesystem can include a computing subsystem configured to perform a cellculture process on the cell culture. The cell culture process can becomputed based on analysis of images acquired by the cell imagingsubsystem and/or based on user input (e.g., user selection of a cellcolony for destruction or removal based on image analysis indicating thecolony as being low quality or undesirable). The image analysis may beperformed using one or more machine learning models or algorithmstrained to evaluate quality of a cell and/or colony based on featuresdetermined to be predictive. The computing subsystem can control a cellediting subsystem to perform the cell culture process. The cell cultureprocess may include addition of fresh media, removal of old media,mixing of media within the cell culture container, poration of targetcell membranes (e.g., to enable cellular internalization ofreprogramming vector(s)), lysis of target cells or cell colonies,removal of lysed cells or cellular debris, detachment of one or moretarget cells, collection of detached cells for further non-imaginganalysis (e.g., qPCR for gene expression analysis). The cell cultureprocess can be carried out by the cell editing subsystem using one ormore mechanisms such as laser, ultrasound, physical/mechanical (e.g.,magnetic tool), or any combination thereof. The cell culture containeror chamber can be configured within a modular cell culture cassettecapable of maintaining a cell culture for extended periods of timewithin a closed sterile environment without breaching that closedenvironment. The cell culture system can be a modular cell culturesystem comprising multiple cell culture cassettes that are stored andmaintained within a supporting structure, wherein each cassette can beused to generate a desired cell product. When the cell culture cassettesare configured as closed cell culture environments, their modular natureenables multiple different cell products to be produced withoutrequiring a clean room or only requiring one clean room to store thesupporting structure comprising the plurality of modular cell culturecassettes. Each subsystem described herein can be used independently toachieve an improvement of the conventional cell culture process.

Additional implementations disclosed herein include an imaging system.The imaging system can be a standalone system for imaging cell cultureor an integrated subsystem of an overall platform or cell culturesystem. In some implementations, the imaging system includes a cellculture moving relative to the imaging system along a direction ofmovement, a light source that illuminates the cell culture, one or moresensors configured to detect a plurality of light signals, and amechanism disposed between the cell culture surface and the sensorconfigured to generate the plurality of light signals from lighttransmitted or reflected by the cell culture, wherein the plurality oflight signals are representative of cell location and refractive indexstructure data.

Another aspect provided herein is an imaging and scanning system,comprising: at least one light source illuminating a cell culture samplehaving cells grown on a growth plane of the cell culture sample; anobjective capturing light from the at least one light source passingthrough the cell culture sample, wherein the objective it tilted at anangle with respect to a perpendicular axis of the growth plane; and oneor more sensors to measure the light from the objective; wherein thecell culture sample is moved relative to the imaging and scanning systemsuch that the imaging system generates images at multiple heights alongthe perpendicular axis of the growth plane. In some implementations, thesystem further comprises: a laser pulse generated by a laser source andincident on the cell culture sample; and an acousto-opticdeflector/modular to adjust an incident angle of the laser pulserelative to the perpendicular axis of the growth plane; wherein the cellculture sample is moved relative to the imaging and scanning system suchthat the laser pulse is capable of focusing on any part of the growthplane. The imaging and scanning system can be a standalone system forimaging and scanning cell culture or an integrated subsystem of anoverall platform or cell culture system.

Another aspect provided herein is a cell culture chamber, comprising:fluid media between a first wall and a second wall, wherein the secondwall is flexible; a cell culture adherent or semi-adherent on the insideof the first wall; and a first actuator configured to push against thesecond wall to create a constricted region in the cell culture chamber;and a mechanism to create a high velocity flow through the constrictedregion, causing dislodging of cells or cell debris from the first wall.In some implementations, the mechanism comprises a pump that pumps thefluid media through the constricted region. In some implementations, thecell culture chamber is sealed and the mechanism comprises a secondactuator that pushes against the second wall to force the fluid mediathrough the constricted region. The cell culture chamber can be astandalone chamber used for cell culturing or an integrated component ofan overall platform or cell culture system.

Another aspect provided herein is a cell culture chamber, comprising:fluid media between a first wall and a second wall, wherein the secondwall is flexible; a cell culture adherent or semi-adherent on the insideof the first wall; and at least one acoustic transducer configured toapply acoustic waves to the cell culture chamber, causing dislodging ofcells or cell debris from the first wall. In some implementations, theat least one acoustic transducer is located on the outside of the cellculture chamber proximate to the first wall and applies the acoustictowards the first wall in a direction perpendicular to a plane of thefirst wall. In some implementations, the at least one acoustictransducer comprises two acoustic transducers coupled to the outside ofthe first wall and configured to create local distortions perpendicularto the plane of the first wall using the acoustic waves.

Further implementations include a method of controlling a cell culturesystem, including receiving, at a plurality of points of time, aplurality of images of a cell culture, identifying a plurality of cellsfrom the plurality of images, identifying one or more cell colonies fromthe plurality of cells, tracking the one or more cell colonies throughthe plurality of points of time, predicting an outcome of the one ormore cell colonies, and editing the cell culture based on the predictedoutcomes of the one or more cell colonies.

Another aspect provided herein is a method of classifying image data ina cell culture system, comprising: growing one or more cell cultures ofa first cell type; obtaining image data of the one or more cellcultures; generating, by an unsupervised learning engine, a plurality ofvisual categories for the first cell type from the image data;associating, by the unsupervised learning engine, the plurality ofvisual categories with a plurality of attribute categories; andlabeling, by an unsupervised inference engine, the image data with theplurality of attribute categories. In some implementations, the imagedata is label-free. In some implementations, the method furthercomprises: acquiring assay data from the one or more cell cultures; andutilizing the assay data to associate the plurality of visual categorieswith a plurality of attribute categories. In some implementations, themethod further comprises: obtaining labeled image data of the one ormore cell cultures; and utilizing the labeled image data to associatethe plurality of visual categories with a plurality of attributecategories.

Another aspect provided herein is a method producing cells in a cellculture system, comprising: growing one or more cell cultures of a firstcell type; obtaining image data of the one or more cell cultures;generating, by an unsupervised inference engine, one or more attributemaps from the image data, wherein each attribute map comprises an imageof a cell culture annotated with cell attributes; determining one ormore actions based on the one or more attribute maps. In someimplementations, the cell attributes are associated with visualcategories identifiable in the image data. In some implementations, theone or more actions comprise lysing select cells in the one or more cellcultures, collecting assays on select cells in the one or more cellcultures, or changing parameters of cell growth of the one or more cellcultures.

Provided herein is a cell culture system, comprising: a cell culturechamber having a first surface; one or more cells in an interior of thecell culture chamber and adhered to the first surface; an imagingsubsystem configured to collect images of the one or more cells; acomputing subsystem configured to select a subset of cells for analysisbased on the images; a cell editing subsystem for dislodging the subsetof cells from the first surface; a mechanism to remove the subset ofcells from the cell culture chamber for analysis.

Another aspect provided herein is a method of cell extraction andanalysis in a cell culture system, comprising: growing a cell culture ina cell culture container; obtaining one or more images of the cellculture; identifying one or more cells to extract from the cell culturebased on the one or more images; extracting the identified cells fromthe cell culture chamber; and analyzing the extracted cells. In someimplementations, the method further comprises adjusting a cell cultureprocess for the cell culture based on the analysis. In someimplementations, the steps of growing, obtaining, extracting, andanalyzing is performed by an automated cell culture system. In someimplementations, the step of identifying is performed by a person.

Another aspect provided herein is a cell culture chamber, comprising: acell bearing surface; a plurality of cells grown on the cell bearingsurface; and a resonant optical film located on the cell bearingsurface. In some implementations, the resonant optical film absorbs morethan 5% of incident light at a cell editing optical wavelength. In someimplementations, the resonant optical film absorbs less than 20% ofincident light at a cell imaging optical wavelength. In someimplementations, the resonant optical film has physical features smallerthan 50% of the cell imaging optical wavelength. In someimplementations, there is a foil with a resonant optical film on thecell bearing surface, the foil inserted into the cell culture chamber.In some implementations, the foil is a membrane with pores. In someimplementations, the resonant optical film has a resonant absorptionpeak at 532 nanometers (nm) and/or 1064 nm. In some implementations, theresonant optical film comprises gold nano-islands attached to anoptically transparent material selected from the following: glass,cyclic olefin copolymer, polystyrene, polycarbonate, polyethyleneterephthalate. In some implementations, the gold nano-islands have amean diameter less than 50 nm along at least one axis.

Another aspect disclosed herein is a cassette system for cell cultureprocessing, comprising: a) one or more cell culture chambers, each cellculture chamber configured to: i) provide a growth environment foradherent cell cultures; and ii) allow imaging of the adherent cellcultures grown in the cell culture chamber; and b) a liquid systemcoupled to the one or more cell culture chambers, wherein the liquidsystem is configured to: i) provide input fluid media to the one or morecell culture chambers; and ii) receive output fluid media from the oneor more cell culture chambers; wherein the liquid system is configuredto provide a closed, sterile liquid environment for the adherent cellcultures in each cell culture chamber. In some implementations, at leastone of the input fluid media and the output fluid media comprises atleast one of growth media, reagents, buffers, fluid waste, and cellcollection media. In some implementations, the liquid system comprisesone or more reservoirs for holding different types of fluid media. Insome implementations, the cassette system further comprises at least onepump for directing the input fluid media, the output fluid media, orboth through the liquid system. In some implementations, the at leastone pump is bidirectional. In some implementations, each cell culturechamber comprises a first semi-transparent surface to allow for imagingof the adherent cell cultures. In some implementations, each cellculture chamber is further configured to allow removal of cells from thecell culture chamber using a cell editing mechanism. In someimplementations, the cell editing mechanism is configured to directlaser energy, ultrasound, or mechanical forces upon the cell culturechamber to effectuate removal of cells. In some implementations, thelaser energy comprises pulsed laser light. In some implementations, thefirst semi-transparent surface comprises a coating configured to absorbthe laser energy at one or more wavelengths and convert the laser energyinto thermal or mechanical energy to remove cells. In someimplementations, at least one of the one or more cell culture chambershas a cell growth area of at least 50 cm². In some implementations, atleast one of the one or more cell culture chambers is completely filledwith fluid media. In some implementations, an internal height of atleast one of the one or more cell culture chambers is less than 1millimeter. In some implementations, the system further comprises: a)one or more sensors; and b) a processor configured to communicate withthe one or more sensors and a process module hosting the cassette systemvia a pluggable connector. In some implementations, the cassette systemis removably coupled to the process module. In some implementations, thecassette system is configured for insertion into the process module in afirst orientation, a second, inverted orientation, or both. In someimplementations, the one or more sensors comprise a temperature sensor,a humidity sensor, a gas-phase oxygen concentration sensor, a gas-phasecarbon dioxide concentration sensor, a dissolved oxygen concentrationsensor, a dissolved carbon dioxide concentration sensor, a gas flow ratesensor, a liquid flow rate sensor, a pH sensor, an optical absorptionsensor, an optical scattering sensor, a mass spectroscopic sensor, aviscosity sensor, or any combination thereof. In some implementations,each cell culture chamber comprises a gas-permeable surface. In someimplementations, the liquid system provides the input fluid media,receives the output fluid media, or both, via a one-time asepticconnector, a one-time aseptic disconnector, a reusable non-asepticconnector, or any combination thereof. In some implementations, thesystem further comprises a mixing and exchange section configured to: a)mix a circulated fluid comprising the input fluid, the output fluid, orboth; b) control a concentration of a dissolved gas in the circulatedfluid; or c) control a temperature of the one or more cell culturechambers. In some implementations, the mixing and exchange sectioncomprises a liquid feedback mechanism, a gas exchange mechanism, orboth. In some implementations, the system further comprises a sensingsection configured to monitor a condition of the input fluid media, theoutput fluid media, or both. In some implementations, the liquid systemis configured to provide the input media to each cell culture chamber ata velocity flow that applies a continuous or directional shear stress ofless than about 10 dyne/cm² to the adherent cell culture. In someimplementations, each adherent cell culture chamber comprises aregistration mark, and wherein the imaging of the adherent cell culturescaptures an image of the registration mark. In some implementations, thecassette system comprises a single-use portion and a permanent portioncomprising a reusable housing enclosing the single-use portion, whereinthe single-use portion comprises the one or more cell culture chambersand the liquid system. In some implementations, the single-use portioncomprises one or more bags or chambers for holding media reagents, wasteproducts, or cellular products. In some implementations: a) the inputfluid media is provided to the one or more cell culture chambers via afirst valve; b) the output fluid media is received from the one or morecell culture chambers via a second valve; or c) both. In someimplementations, imaging the cell cultures comprises transmissionimaging, reflection imaging, brightfield imaging, darkfield imaging,phase imaging, differential interference contrast (DIC) imaging,quantitative phase imaging (QPI), transmission Fourier ptychographicimaging, reflection transmission Fourier ptychographic imaging,holographic imaging, or any combination thereof.

Another aspect disclosed herein is a cell culture system, comprising: a)a cell culture chamber having a first surface, a second surface, and aninterior between the first surface and the second surface; b) aplurality of cells in the interior of the cell culture chamber andadhered to the first surface; c) a magnetic tool in the interior of thecell culture chamber; d) a magnetic component located exterior to thecell culture chamber, the magnetic component magnetically coupled to themagnetic tool; and e) an actuator removably coupled to the magneticcomponent and configured to move the magnetic component in one or moredirections, wherein moving the magnetic component also moves themagnetic tool in the same manner. In some implementations, the actuatoris configured to translate and/or rotate the magnetic component, therebytranslating and/or rotating the magnetic tool. In some implementations,the translation and/or rotation of the magnetic tool inside the cellculture chamber agitates fluid media inside the cell culture chamber. Insome implementations, the agitation dislodges cells, cell components, orcell products from the first surface and/or moves cells, cellcomponents, or cell products floating in the fluid media around the cellculture chamber. In some implementations, the magnetic tool makesphysical contact with one or more cells in the plurality of cells todislodge them from the first surface. In some implementations, thesystem further comprises an imaging subsystem configured to captureimages of the plurality of cells. In some implementations, the systemfurther comprises a computing subsystem configured to: a) identify oneor more cells in the plurality of cells for removal based on the images;and b) control the actuator to move the magnetic tool to remove the oneor more cells. In some implementations, the imaging system is furtherconfigured to capture images of the magnetic tool. In someimplementations, the computing subsystem identifies the one or morecells using a machine learning algorithm. In some implementations, thecomputing subsystem is further configured to control a velocity, anorientation, a path, or any combination thereof of the actuator. In someimplementations, the computing subsystem is further configured tocontrol a magnetic pole alignment of the actuator. In someimplementations, the computing subsystem is further configured to: a)engage the actuator with the first surface of the cell culture chamber;b) engage the actuator with the second surface of the cell culturechamber; c) disengage the actuator with the first surface of the cellculture chamber; d) disengage the actuator with the second surface ofthe cell culture chamber; or e) any combination thereof. In someimplementations, the system further comprises a cell culture containerenclosing the cell culture chamber, wherein the cell culture containercontrols fluid media into and out of the cell culture chamber in aclosed loop, sterile environment. In some implementations, the cellculture container encloses a plurality of cell culture chambers. In someimplementations, the magnetic tool contacts the first surface and themagnetic component rests on the exterior of the first surface. In someimplementations, the magnetic tool contacts the second surface and themagnetic component rests on the exterior of the second surface. In someimplementations, at least a portion of the magnetic tool and/or magneticcomponent is coated with a polymer. In some implementations, the polymeris configured to make a surface of the magnetic tool and/or magneticcomponent that contacts the cell culture chamber inert, biocompatible,non-stick, non-scratching, or any combination thereof. In someimplementations, the cell culture chamber has a growth area of at leastabout 50 cm². In some implementations, the cell culture chamber has achamber height of less than about 3 mm. In some implementations, themagnetic tool further comprises a blade configured to lift one or moreof the plurality of cells from the first surface, the second surface, orboth. In some implementations, the blade comprises a low angle edgeconfigured for non-destructive incremental lifting of one or more of theplurality of cells. In some implementations, the blade comprises a highangle edge configured to lyse and/or destroy one or more of theplurality of cells. In some implementations, at least a portion of themagnetic tool is flexible.

Another aspect disclosed herein is a modular bioprocessing system,comprising: a) one or more process modules, each process moduleconfigured to manage and monitor a cell culture process; b) a serverrack, wherein the one or more process modules are removably located onthe server rack; and c) one or more shared subsystems on the server rackand supporting the one or more process systems. In some implementations,each process module is configured to removably couple to a cell culturecassette hosting the cell cultures via one or more pluggable connectors.In some implementations, the cell culture process is carried out withina cell culture container comprising a closed cassette system, a microplate, a flask, a cell culture vessel, a microfluidic chamber, or anycombination thereof. In some implementations, the system furthercomprises a transport mechanism configured to transport the cell culturecontainer between locations within the server rack. In someimplementations, the transport mechanism comprises a rail, a linearactuator, a motor, a bearing, a wheel, or any combination thereof. Insome implementations, the transport mechanism is configured to providehorizontal and/or vertical transportation of the cell culture container.In some implementations, the closed cassette system comprises at leastone transparent or semi-transparent surface that allows for light orlaser-based imaging and editing. In some implementations, the systemfurther comprises a front-facing instrument panel configured to receiveand/or eject the closed cassette system, the micro plate, the flask, thecell culture vessel, the microfluidic chamber, or any combinationthereof. In some implementations, the one or more shared subsystemscomprise at least one of a computing subsystem, a data storagesubsystem, an environmental control subsystem, a laser source subsystem,and a gas distribution subsystem. In some implementations, the one ormore process modules comprises at least one of a cell imaging subsystem,a cell editing subsystem, and a temperature control subsystem. In someimplementations, the cell imaging subsystem comprises a brightfieldimaging system, a phase imaging system, a quantitative phase imagingsystem, a transmissive darkfield imaging system, a reflective darkfield,imaging system, a fluorescent imaging system, or any combinationthereof. In some implementations, the cell imaging subsystem isconfigured to capture images of the cell culture process. In someimplementations, the one or more shared subsystems comprises a computingsubsystem configured to perform a machine learning function to monitorthe cell culture process based on the images. In some implementations,the cell editing subsystem is configured to selectively remove one ormore cells from the cell culture process. In some implementations, theserver rack has one or more standardized computer server rack sizes. Insome implementations, the system further comprises a backup power modulefor providing uninterrupted power to the one or more process modules andthe one or more shared subsystems. In some implementations, the systemfurther comprises a temperature control subsystem configured to manage atemperature of at least one of the cell culture process and a reagent.In some implementations, the system further comprises a pH controlsubsystem configured to manage a pH of the cell culture process. In someimplementations, the system further comprises a gas content controlsubsystem configured to manage a dissolved oxygen and/or carbon dioxidecontent of at least one of the cell culture process and a reagent. Insome implementations, the system further comprises a media controlsubsystem configured to provide and/or extract a media from at least oneof the one or more process modules. In some implementations, the cellculture process comprises cell reprogramming, cell differentiation, cellgene editing, cell incubation, cell expansion, cell sorting orpurification, cell-based bioproduction, or any combination thereof. Insome implementations, the modular bioprocessing system has a multi-rackconfiguration comprising a plurality of the server rack.

Another aspect disclosed herein is an imaging system, comprising: a) atleast one light source illuminating a sample; b) an objective capturinglight from the at least one light source passing through the sample; andc) one or more sensors to measure the light captured by the objective,wherein the sample moves continuously relative to the at least one lightsource and the objective during the measurement; and d) a computingsubsystem configured to generate quantitative phase images of the samplebased on the measurements from the one or more sensors. In someimplementations, the movement of the sample relative to the at least onelight source and the objective during the measurement generates imagedata at multiple focal planes along an axis perpendicular to ahorizontal plane of the sample and the quantitative phase images aregenerated from the image data at multiple focal planes. In someimplementations, the objective is tilted at an angle with respect to theaxis. In some implementations, the movement of the sample relative tothe at least one light source and the objective during the measurementgenerates image data at multiple illumination angles relative to thesample and the quantitative phase images are generated from the imagedata at multiple illumination angles. In some implementations, the atleast one light source emits light at multiple wavelengths and differentwavelengths illuminate the sample at different angles. In someimplementations, the system further comprises a laser source configuredto manipulate the sample based on the quantitative phase images. In someimplementations, the sample is moved continuously relative to the lasersource. In some implementations, the laser source and the one or morelight sources share the objective. In some implementations, the sampleis a cell culture sample and the laser source is configured to edit thecell culture sample. In some implementations, the cell culture sample isenclosed in a cell culture chamber, the cell culture chamber comprisingat least one transparent or semi-transparent surface. In someimplementations, the cell culture chamber comprises a transparent upperwindow and a transparent lower window. In some implementations, the cellculture chamber comprises at least one semi-transparent coating on theat least one transparent surface configured to absorb laser radiationand direct absorbed energy to one or more cells in the cell culturechamber. In some implementations, the system further comprises a filmwithin the cell culture chamber, wherein the film comprises a fiducialmarker and wherein the fiducial marker is patterned in the laserabsorbing film. In some implementations, the laser source is configuredto generate a laser having a wavelength of about 500 nm to about 600 nmor about 1000 nm to about 1100. In some implementations, the lasersource is configured to generate a laser having a pulse rate of at leastabout 100 kHz. In some implementations, the system further comprises alaser autofocus system configured to: a) project a laser from the lasersource onto the cell culture; b) move the sample relative to the lasersource; c) repeat steps a) and b); d) measure a sharpness of the laserbased on the light captured by the objective lens during steps a)-c);and e) focus the laser based on the measured sharpness. In someimplementations, the sensor comprises a CMOS sensor, a CCD sensor, orboth. In some implementations, the sensor comprises an array of sensorsin one or more directions. In some implementations, the computingsubsystem is configured to compute structural information on individualcells, groups of cells, or regions or colonies using the quantitativephase images of the sample. In some implementations, the computingsubsystem is configured to apply machine learning to analyze themeasurements from the one or more samples. In some implementations, thecomputing subsystem is configured to use a convolutional neural networkto reconstruct sample amplitude and phase. In some implementations, thecomputing subsystem is configured to use a convolutional neural networkto reconstruct sample amplitude and phase or determine one or more cellquality features. In some implementations, wherein the system comprisesa first light source and a second light source, wherein the first lightsource and the second light source emit light at different wavelengths.

Another aspect disclosed herein is a method for generating quantitativephase images of a sample, comprising: a) illuminating a sample using atleast one light source; b) capturing, with an objective, light from theat least one light source passing through the sample; and c) measuring,with one or more sensors, the light captured by the objective, whereinthe sample moves continuously relative to the at least one light sourceand the objective during the measurement; and d) generating, with acomputing subsystem, quantitative phase images of the sample based onthe measurements from the one or more sensors.

Another aspect disclosed herein is a monoclonal induced pluripotent stemcell (iPSC) product made by the process comprising: a) placing inputcells in a cell culture chamber of a closed cell culture container; b)reprogramming at least a portion of the input cells into a plurality ofclonal iPSC candidate cells; c) collecting imaging data on a pluralityof clonal iPSC candidate cell colonies emerging from the plurality ofclonal iPSC candidate cells; d) selecting one of the plurality of clonaliPSC candidates cell colonies for expansion based on the imaging data;e) removing non-selected clonal iPSC candidate cell colonies using acell editing mechanism; and f) expanding the selected clonal iPSCcandidate cell colony into the monoclonal iPSC product. In someimplementations, the imaging data comprises a time-series images of theplurality of clonal iPSC candidate cell colonies. In someimplementations, selecting one of the plurality of clonal iPSCcandidates cell colonies for expansion comprises: a) applying apredictive model to the image data to predict clonal quality andfunctionality of each of the plurality of clonal iPSC candidate cellcolonies; and b) selecting one of the plurality of clonal iPSCcandidates cell colonies based on the predicted clonal quality andfunctionality of each of the plurality of clonal iPSC candidate cellcolonies. In some implementations, the predictive model is trained onprior clonal cell colony data and clonal iPSC product quality andfunctionality assays. In some implementations, the clonal quality andfunctionality are determined by based on one or more phenotypicfeatures. In some implementations, the one or more phenotypic featurescomprise a cell morphology, a cell proliferation rate, a chromatincondensation, a nucleus to cytosol ratio, a cell migration pattern, orany combination thereof. In some implementations, the process furthercomprises removing contaminant cells in proximity to the plurality ofclonal iPSC candidate cell colonies using the cell editing mechanism. Insome implementations, the closed cell culture container furthercomprises a sterile-sealed liquid system for providing fluid media tothe cell culture chamber and receiving fluid media from the cell culturechamber. In some implementations, the cell editing mechanism compriseslaser radiation. In some implementations, a surface of the cell culturechamber is laser-absorbant. In some implementations, the cell editingmechanism comprises a magnetic tool in the cell culture chamber andactuated from outside the cell culture chamber. In some implementations,the magnetic tool comprises a rare-earth magnet. In someimplementations, the cell editing mechanism comprises focused ultrasoundwaves. In some implementations, the cell editing mechanism comprisesdirected energy projected from outside the cell culture chamber. In someimplementations, the closed cell culture container comprises a singleclosed cell culture container. In some implementations, the one or moreof the input cells comprise a B lymphocytes cell, a blood-derivedepithelial cell, a C lymphocytes cell, a cardiac muscle cell, achondrocyte cell, an endothelial cell, an epidermal cell, an epithelialcell, an erythrocyte cell, a fibroblast cell, a granulosa epithelialcell, a hair follicle cell, a hematopoietic cell, a hepatocyte cell, akeratinocyte cell, a macrophage cell, a melanocyte cell, a monocytecell, a mononuclear cell, a neuron cell, a pancreatic islet cell, asertoli cell, a somatic cells, a urine-derived epithelial cell, or anycombination thereof. In some implementations, the reprogramming isperformed using genome integration, non-genome integration, minicirclevectors, the Sendai protocol, mRNA, self-replicating RNA, CRISPRactivators, recombinant proteins, or any combination thereof. In someimplementations, the monoclonal iPSC product is transgene-free. In someimplementations, the monoclonal iPSC product is suitable fordifferentiation into a target cell type. In some implementations, thenon-selected clonal iPSC candidate cell colonies are determined based onat least a cell division time, a cell high reprogramming cargo load, acell migration characteristic, a cell speed, a cell trackability, or anycombination thereof. In some implementations, the process is performedwithin a cassette system providing a closed, sterile environment forcell culture processing. In some implementations, the process isperformed within a modular bioprocessing system configured to produce aplurality of monoclonal iPSC products corresponding to differentsubjects.

Another aspect disclosed herein is a method for producing a monoclonalinduced pluripotent stem cell (iPSC) product, comprising: a) placinginput cells in a cell culture chamber of a closed cell culturecontainer; b) reprogramming at least a portion of the input cells into aplurality of clonal iPSC candidate cells; c) collecting imaging data ona plurality of clonal iPSC candidate cell colonies emerging from theplurality of clonal iPSC candidate cells; d) selecting one of theplurality of clonal iPSC candidates cell colonies for expansion based onthe imaging data; e) removing non-selected clonal iPSC candidate cellcolonies using a cell editing mechanism; and f) expanding the selectedclonal iPSC candidate cell colony into the monoclonal iPSC product.

BRIEF DESCRIPTION OF THE DRAWINGS

The novel features of the disclosure are set forth with particularity inthe appended claims. A better understanding of the features andadvantages of the present disclosure will be obtained by reference tothe following detailed description that sets forth illustrativeimplementations, in which the principles of the disclosure are utilized,and the accompanying drawings of which:

FIG. 1 is a block diagram of a cell culture system in accordance withvarious implementations;

FIG. 2 is a flow chart of a method of operating a cell culture system inaccordance with various implementations;

FIG. 3 are graphs illustrating how cell features may be observed atdifferent focus planes in a brightfield illuminated cell culture inaccordance with various implementations;

FIG. 4 is a block diagram of an example imaging subsystem of a cellculture system in accordance with various implementations;

FIG. 5 are graphs illustrating the imaging of a single cell using amulti-focus imaging subsystem in accordance with variousimplementations;

FIG. 6 is a block diagram of another example imaging subsystem of a cellculture system in accordance with various implementations;

FIG. 7 is a block diagram of another example imaging subsystem of a cellculture system in accordance with various implementations;

FIG. 8 is a diagram of an example implementation of a multi-focusdiffractive element and a detector in accordance with variousimplementations;

FIG. 9 is a diagram of another example implementation of a multi-focusdiffractive element and a detector in accordance with variousimplementations;

FIG. 10A is a block diagram of an extension of the imaging subsystemshown in FIG. 7 in accordance with various implementations;

FIG. 10B shows an exemplary autofocus output from a system utilizing a532 nm pulsed laser in accordance with various implementations; and

FIG. 11 is a block diagram of an imaging subsystem combined with a cellediting subsystem in accordance with various implementations;

FIG. 12 is a block diagram of an imaging subsystem in accordance withvarious implementations;

FIG. 13 is a block diagram of a wavelength separation subsystem in animaging subsystem in accordance with various implementations;

FIG. 14 is a block diagram of another multi-wavelength light source inan imaging subsystem in accordance with various implementations;

FIG. 15 is a block diagram of a multi-wavelength light source in animaging subsystem in accordance with various implementations;

FIG. 16 is a block diagram of another multi-wavelength light source inan imaging subsystem in accordance with various implementations;

FIG. 17 is a block diagram of another multi-wavelength light source inan imaging subsystem in accordance with various implementations;

FIG. 18 is a diagram of a tilt-defocused cell culture imaging andediting system in accordance with various implementations;

FIG. 19 is a cross-section of a cell culture chamber duringtilt-defocused imaging and/or laser scanning in accordance with variousimplementations;

FIGS. 20A-C are imaging field views of a tilt-defocused cell cultureimaging and editing system in accordance with various implementations;

FIGS. 21A-C are diagrams illustrating a portion of a process for iPSCreprogramming in accordance with various implementations;

FIGS. 22A-B are diagrams illustrating cell removal during an iPSCreprogramming process in accordance with various implementations;

FIGS. 23A-C are diagrams illustrating cell isolation during an iPSCreprogramming process in accordance with various implementations;

FIGS. 24A-C are images illustrating cell isolation during an iPSCreprogramming process in accordance with various implementations;

FIGS. 25A-C are diagrams illustrating non-iPS cell removal during aniPSC reprogramming process in accordance with various implementations;

FIGS. 26A-B are diagrams illustrating neighboring cell removal aroundiPSC colonies during an iPSC reprogramming process in accordance withvarious implementations;

FIGS. 27A-B are diagrams illustrating removal of cells that break offfrom iPSC colonies during an iPSC reprogramming process in accordancewith various implementations;

FIGS. 28A-B are diagrams illustrating removal of non-iPS cell candidatesduring an iPSC reprogramming process in accordance with variousimplementations;

FIGS. 29A-C are diagrams illustrating removal of a cell colony during aniPSC reprogramming process in accordance with various implementations;

FIGS. 30A-B are images illustrating removal of a cell colony during aniPSC reprogramming process in accordance with various implementations;

FIGS. 31A-C are diagrams illustrating selection of a cell colony duringan iPSC reprogramming process in accordance with variousimplementations;

FIGS. 32A-C are diagrams illustrating spreading of a cell colony in acell culture chamber during an iPSC reprogramming process in accordancewith various implementations;

FIGS. 32D-32E show an initial colony controlled for density that spreadover a growth chamber in accordance with various implementations;

FIGS. 33A-B are diagrams illustrating removal of cells outside ofdesignated regions during an iPSC reprogramming process in accordancewith various implementations;

FIGS. 34A-C are images illustrating removal of various cells during aniPSC reprogramming process in accordance with various implementations;

FIGS. 35A-C are diagrams illustrating fragmenting of a cell colony in acell culture chamber during an iPSC reprogramming process in accordancewith various implementations;

FIGS. 36A-B are images illustrating fragmenting of a cell colony in acell culture chamber during an iPSC reprogramming process in accordancewith various implementations;

FIG. 36C shows a dense hiPSC cell culture removed using lasermicrobubble lysing and washing in accordance with variousimplementations;

FIG. 36D shows regrowth of the hiPSC cell culture after 24 hours inaccordance with various implementations;

FIGS. 37A-C are diagrams illustrating harvesting of cells in a cellculture chamber during an iPSC reprogramming process in accordance withvarious implementations;

FIGS. 38A-38B are block diagrams of a closed cell culture container witha magnetic tool in accordance with various implementations;

FIG. 38C shows dye in a liquid chamber of an exemplary micro-magnetictool in accordance with various implementations;

FIG. 38D shows an exemplary micro-magnetic tool being translated throughliquid from right to left by an actuator external to liquid chamber inaccordance with various implementations;

FIG. 38E shows an exemplary micro-magnetic tool being translated throughliquid from right to left and counter-clockwise by an actuator externalto liquid chamber in accordance with various implementations;

FIG. 39 is a three-dimensional view of a closed cell culture containerwith a magnetic tool in accordance with various implementations;

FIG. 40A is a block diagram of various modes of use for a magnetic toolin a closed cell culture container in accordance with variousimplementations;

FIG. 40B illustrates rotation of an internal magnetic tool in a closedcell culture chamber in accordance with various implementations;

FIGS. 41A-41B illustrate use of an internal magnetic tool in a cellculture chamber for mixing media in accordance with variousimplementations;

FIGS. 42A-42C illustrate use of an internal magnetic tool in a cellculture chamber for removing debris in accordance with variousimplementations;

FIGS. 43A-43D also illustrates use of an internal magnetic tool in acell culture chamber for removing debris in accordance with variousimplementations;

FIG. 44 is a block diagram of a closed cell culture container with amagnetic tool in accordance with various implementations;

FIG. 45A illustrates various views of an internal magnetic tool for useon a cell-bearing surface in accordance with various implementations;

FIG. 45B illustrates another internal magnetic tool for use on acell-bearing surface in accordance with various implementations;

FIGS. 46A-C illustrate examples of cell editing functions provided by aninternal magnetic tool in accordance with various implementations;

FIG. 47A illustrates cross-sectional views of examples of cell editingfunctions provided by an internal magnetic tool in accordance withvarious implementations;

FIG. 47B illustrates an example of cell editing functions provided by analternate internal magnetic tool in accordance with variousimplementations;

FIGS. 48A-K illustrate cell editing operations conducted by an internalmagnetic tool during cell culturing in accordance with variousimplementations;

FIGS. 49A-I illustrate cross-sectional views of cell editing operationsconducted by an internal magnetic tool during cell culturing inaccordance with various implementations;

FIGS. 50A-B illustrates an alternate implementation of an internalmagnetic tool in accordance with various implementations;

FIG. 50C Illustrates the operating concept of the 2-sided magnetic tool,with actuators on both sides of a cell culture chamber in accordancewith various implementations;

FIGS. 51A-51C illustrates ultrasound lysis of cells in a cell culturesystem in accordance with various implementations;

FIG. 52A illustrates an alternate method of ultrasound lysis of cells ina cell culture system in accordance with various implementations;

FIG. 52B illustrates a combined imaging and ultrasound lysing system ina cell culture system in accordance with various implementations;

FIGS. 53A-53B illustrate a mechanical method of washing away cells andcell debris from a closed cell culture chamber in accordance withvarious implementations;

FIGS. 54A-54B illustrate another mechanical method of washing away cellsand cell debris from a closed cell culture chamber in accordance withvarious implementations;

FIGS. 55A-55B illustrate a method for dislodging cells and cell debrisin a closed cell culture chamber in accordance with variousimplementations;

FIG. 56 illustrates another method for dislodging cells and cell debrisin a closed cell culture chamber in accordance with variousimplementations;

FIG. 57A is a block diagram of a computing subsystem in a cell culturesystem in accordance with various implementations;

FIG. 57B is a flow chart of a method of controlling a cell culture inaccordance with various implementations;

FIG. 58A shows an exemplary normalized brightfield z-stack image of ahiPSC colony in accordance with various implementations;

FIG. 58B shows an exemplary output of a deep learning neural networkthat has been trained to predict nuclear stains from brightfieldz-stacks, after thresholding in accordance with various implementations;

FIG. 58C shows a first exemplary brightfield image z-stack slice of ahiPSC colony proliferating over about 65 hours in accordance withvarious implementations;

FIG. 58D shows the image of FIG. 58A with polygons delineatingdetermined colony areas in accordance with various implementations;

FIG. 58E shows a second exemplary brightfield image z-stack slice of ahiPSC colony proliferating over about 65 hours in accordance withvarious implementations;

FIG. 58F shows the image of FIG. 58C with polygons delineatingdetermined colony areas in accordance with various implementations;

FIG. 58G shows a third exemplary brightfield image z-stack slice of ahiPSC colony proliferating over about 65 hours in accordance withvarious implementations;

FIG. 58H shows the image of FIG. 58E with polygons delineatingdetermined colony areas in accordance with various implementations;

FIG. 59 is a block diagram of an automated classification system in acell culture system in accordance with various implementations;

FIG. 60 is a block diagram of components in an automated classificationsystem in accordance with various implementations;

FIG. 61 is a block diagram of an automated classification systemlearning to associate visual categories to cell attribute categories bymeans of a cell lysing and assay methodology in accordance with variousimplementations;

FIG. 62 is a block diagram showing an example association of visualcategories to attribute categories in accordance with variousimplementations;

FIG. 63 is a block diagram of an automated classification systemlearning the association of visual categories to cell attributecategories via selective staining and labeled imaging in accordance withvarious implementations;

FIG. 64 is a block diagram showing manufacturing of cells using anautomated classification system in accordance with variousimplementations;

FIG. 65 is a flow chart of a method of classifying image data in a cellculture system in accordance with various implementations;

FIG. 66 is a flow chart of a method of growing cells in a cell culturesystem in accordance with various implementations;

FIG. 67 is a diagram of a closed cassette system for use in a cellculture system in accordance with various implementations;

FIG. 68A is a diagram of a cell culture chamber in a closed cassettesystem in accordance with various implementations;

FIG. 68B is an image of an exemplary cell culture chamber in accordancewith various implementations;

FIG. 68C shows an exemplary hiPSCs grown under continuous media flow ina liquid-filled chamber with a height of less than about 1 mm height inaccordance with various implementations;

FIG. 69 is a diagram illustrating removal of cells from a cell culturechamber in a closed cassette system in accordance with variousimplementations;

FIG. 70 is a diagram illustrating agitation of cells from a cell culturechamber in a closed cassette system in accordance with variousimplementations;

FIG. 71 is a diagram of a single-use portion of a closed cassette systemfor use in a cell culture system in accordance with variousimplementations;

FIG. 72 is a diagram of a permanent portion of a closed cassette systemfor use in a cell culture system in accordance with variousimplementations;

FIG. 73 illustrates various cell culture chamber configurations in aclosed cassette system for use in a cell culture system in accordancewith various implementations;

FIG. 74 is a diagram of a modular bioprocessing system in accordancewith various implementations;

FIG. 75 illustrates container transportation functionality in a modularbioprocessing system in accordance with various implementations;

FIG. 76A is another diagram of a modular bioprocessing system inaccordance with various implementations;

FIG. 76B shows an exemplary prototype process module (lower, withhandles) and partially inserted cell culture cassette, which is shownco-located with RAID storage array (with 16 drive bays visible) andbackup power module (above, marked Tripp Lite), in accordance withvarious implementations;

FIG. 77 is a diagram of a modular cell culture system in accordance withvarious implementations;

FIG. 78 is a diagram of a cell culture cassette compatible with amodular cell culture system in accordance with various implementations;

FIG. 79 is another diagram of a cell culture cassette compatible with amodular cell culture system in accordance with various implementations;

FIG. 80 is a diagram of a rack-style modular cell culture system inaccordance with various implementations;

FIGS. 81A-81C are diagrams illustrating cell culturing in a closed cellculture cavity in accordance with various implementations;

FIGS. 82A-82B are diagrams illustrating adherence of cells in a closedcell culture cavity in accordance with various implementations;

FIGS. 83A-83E are diagrams illustrating separation of adherent andsemi-adherent cells in a cell culture cavity in accordance with variousimplementations;

FIGS. 84A-84E are diagrams illustrating removal of semi-adherent cellsin a cell culture cavity in accordance with various implementations;

FIGS. 85A-85E are diagrams illustrating selective separation ofsemi-adherent cells in a cell culture system in accordance with variousimplementations;

FIG. 86 is a flow chart illustrating a method of cell culturing in acell culture system in accordance with various implementations;

FIGS. 87A-87E are diagrams illustrating selective cell extraction andanalysis of adherent cells in accordance with various implementations;

FIGS. 88A-88C are diagrams illustrating selective cell extraction andanalysis of semi-adherent cells in accordance with variousimplementations;

FIGS. 89A-89C are diagrams illustrating a cell culture process withselective cell extraction and analysis in accordance with variousimplementations;

FIG. 90 is a flow chart illustrating a method of cell extraction andanalysis in accordance with various implementations;

FIG. 91 is a graph illustrating the absorption/transmission behavior atdifferent wavelengths of a resonant optical firm in accordance withvarious implementations;

FIG. 92 is an image of a microwell plate with a resonant optical film onthe cell-bearing surface in accordance with various implementations;

FIGS. 93A-93C are images of cells undergoing cell editing and washing ina cell culture chamber having a resonant optical film in accordance withvarious implementations;

FIG. 94 is an image of a resonant optical film surface in accordancewith various implementations;

FIG. 95 is a graph showing the transmission spectrum of an optical filmwhich has resonances at specific wavelengths; and

FIG. 96 shows an exemplary computer system in accordance with variousimplementations.

These and other features of the present implementations will beunderstood better by reading the following detailed description, takentogether with the figures herein described. The accompanying drawingsare not intended to be drawn to scale. For purposes of clarity, notevery component may be labeled in every drawing.

DETAILED DESCRIPTION

Disclosed herein are systems and methods including an automated cellculture system that may quickly and accurately produce output cellproducts and that is easily scalable to enable large scale biologicalmanufacturing. The system may include cell imaging subsystems to acquireimages of a cell culture, a cell editing subsystem to edit (e.g.,remove) one or more cells during the cell culture process, a computingsubsystem that controls the cell editing subsystem based on the acquiredimages, or any combination thereof. The computing subsystem may applymachine learning to data collected by the system (e.g., imaging data,sensor data, input and output assay data) to determine how toeffectively edit the cell culture to reach the desired output. Thisallows for dynamic monitoring and control of how the cell culturedevelops from input cells to output cell products. The automated natureof the system removes the need for manual human intervention at manystages of cell culture development, thus reducing the time and cost ofmaking output cell products. It also allows for easy scalability, as thecomputing subsystem may monitor and control multiple cell cultureprocesses at the same time.

FIG. 1 is a block diagram of a cell culture system 100 in accordancewith various implementations. The cell culture system 100 receives inputcells 102 as “source” cells upon which the cell culture system 100performs various cell culture processes. The input cells 102 may besorted, expanded, or otherwise modified prior to the cell cultureperformed by the cell culture system 100. Input cell types may include,but are not limited to, somatic cells (including but not limited tofibroblasts, mature blood and progenitor cells, such as CD34+ cells anderythroblasts, keratinocytes, epithelial cells, including blood andurine-derived epithelial cells, Sertoli cells, endothelial cells,granulosa epithelial, neurons, pancreatic islet cells, epidermal cells,epithelial cells, hepatocytes, hair follicle cells, keratinocytes,hematopoietic cells, melanocytes, chondrocytes, lymphocytes (B and Tlymphocytes), erythrocytes, macrophages, monocytes, mononuclear cells,fibroblasts, cardiac muscle cells, other muscle cells, and generally anylive somatic cells. The term “somatic cells,” as used herein, alsoincludes adult stem cells and pluripotent stem cells (including but notlimited to induced pluripotent stem cells and embryonic stem cells).

The input cells 102 may be analyzed with one or more input cell assays108 which serve to quantify the state of the input cells 102. The inputcell assays 108 may be nondestructive (such as cell counting) or asample may be extracted for tests including, but not limited to, genomicprofiling, gene expression assays such as PCR, qPCR, microarray,single-cell RNA sequencing, whole exome sequencing (WES), whole genomesequencing (WGS), karyotyping, short tandem repeat (STR) analysis,sterility testing (testing for bacteria and viruses), or other phenotypeanalysis including but not limited to cell surface antigen orintracellular staining-based immunofluorescence or flow analysis, andcell viability, morphology and migration assays, or any otherimplementations known to persons of ordinary skill in the art. Thesample extraction can be performed using automated or semi-automatedprocesses within a closed cell culture environment to enable continuedpropagation of the cell culture within a sterile environment. Theresults of these assays are transmitted to a computing subsystem 110,which may use the results in various software applications to monitor,predict, and control the cell culture process performed by the cellculture system 100.

The input cells 102 are placed into a cell culture 104, where they willremain for the duration of the processes performed by the cell culturesystem 100. The cell culture 104 may reside in a cell culture container106. The cell culture container 106 may include one or more chambers tohold the cell cultures, and may take the form of microwell plates,flasks, stackable cell culture containers, closed cassette systems,microfluidic chambers, purpose-built bioreactor vessels, or any otherimplementations known to persons of ordinary skill in the art. The cellculture container 106 may be a closed/sealed sterile environment for thecell culture 104 and fluid media used in cell culture processes.

The cell culture 104 may be used for a number of cell processesperformed and monitored by the cell culture system 100, including butnot limited to: cell reprogramming (into pluripotent or multipotentforms), cell differentiation, cell trans-differentiation, cellexpansion, cell sorting, clonal isolation, cell gene editing, cell-basedprotein production, cell-based viral production, combinations thereof,or any other implementations known to persons of ordinary skill in theart.

The cell culture container 106 may be in a format that allows forobservation of the cell culture 104 at regular intervals using animaging subsystem 112. For example, the cell culture container 106 mayinclude a closed cassette system having at least one transparent orsemi-transparent surface that allows for light or laser-based imagingand editing. The imaging subsystem 112 may be configured to providelabel-free imaging suitable for long-term cell culture observation,although some implementations may include fluorescent imaging capabilityfor immunofluorescent or other labeled images. Label-free modalitiesemployed by the imaging subsystem 112 may include, but are not limitedto, brightfield imaging, phase imaging, darkfield imaging, transmissionimaging, reflection imaging, quantitative phase imaging, holographicimaging, two-photon imaging, autofluorescence imaging, Fourierptychographic imaging, defocus imaging or any other implementationsknown to persons of ordinary skill in the art.

The cell culture system 100 further includes a cell editing subsystem114 for editing the cell culture 104. The cell editing subsystem 114 mayedit the cell culture 104 at a regional, colony-specific, and/orcell-specific level. Editing, in this context, may include selectivedestruction and/or removal of cells or cell regions, and non-destructiveoperations on cells (including intracellular delivery of compounds intocells or extraction of compounds from cells). The cell editing subsystem114 may edit the cell culture 104 through a variety of directed energymechanisms. In other words, the cell editing subsystem 114 may generateenergy that is directly used to edits cells and/or converts energy ofone form (e.g., light, mechanical) into energy of another form toachieve cell editing. The mechanism by which the cell editing subsystem114 acts upon cells in the cell culture may include, but not be limitedto, robotic systems that mechanically actuate a tip or tool across thecell culture, magnetic actuators in conjunction with magnetic tools thatinteract with the cell culture, systems that are configured toselectively apply an electric field across portions of the cell culture,ultrasound systems that are configured to apply ultrasonic energy toportions of the cell culture, droplet or particle ejection/accelerationsystems that are designed to impact droplets or particles on portions ofthe cell culture, optical systems that are designed to deliver opticalenergy to portions of the cell culture, combinations thereof, or anyother implementations known to persons of ordinary skill in the art.

Optical mechanisms for cell editing may include, but are not limited to,optical systems that direct energy directly into cells or surroundingmedia in the cell culture, optical systems that direct energy intoparticles or dyes that are added to the cell culture media (includingbut not limited to particles functionalized in a manner to attach tospecific cells, or that are taken up by cells), or optical systems thatdirect energy into particles or films that are on surfaces proximate toportions of the cell culture, or any other implementations known topersons of ordinary skill in the art. Optical mechanisms may operate onthe cell culture by a number of approaches including, but not limitedto, elevating the local temperature to a point where cells are destroyeddue to heat damage, elevating local temperature to cause boiling and/orbubble formation to cause portions of the cell culture to detach from asurface, or elevating local temperature rapidly in order to cause rapidbubble formation and then subsequent collapse to affect mechanicalforces on the local cell membranes, or combinations thereof.

The cell culture system 100 may also include a number of sensors andcontrols 116 which may measure or act upon the cell culture 104. Forexample, the sensors and controls 116 may carry out functions such asmeasuring media conditions within the cell culture 104, causing freshmedia to be supplied, or adding reagents or gases in order to adjustmedia conditions for optimal cell culture growth. Sensors that sense thestate of the cell culture 104, cell culture media, and/or surroundingcell culture container 106 may include, but are not limited to,temperature sensors, humidity sensors, gas composition sensors includingbut not limited to O₂ and CO₂ concentration sensors, gas flow ratesensors, dissolved gas sensors including but not limited to dissolved O₂sensors, liquid flow rate sensors, and sensors to measure cell culturemedia constituents (such as nutrients, waste products, vitamins,metabolites, proteins, extracellular vesicles, cell mass, or celldebris) including but not limited to optical absorption sensors, opticalscattering sensors, mass spectroscopic sensor systems, optical orelectrical pH sensors, and viscosity sensors.

Controls that may interact with the cell culture 104 or the cell culturecontainer 106 may include, but are not limited to, liquid handlingsystems that inject or extract various liquids to/from the cell culture104 or the cell culture container 106, environmental control systemsthat control the temperature or other environmental parameters of thecell culture 104 or the cell culture container 106, power systems thatprovide electrical power to the cell culture container 106, andmechanical or robotic systems that may move or manipulate the cellculture container 106 or portions thereof.

The computing subsystem 110 may be configured to control the othercomponents of the cell culture system 100 to perform the specified cellculture process on the cell culture 104 to produce output cell products118. The output cell products 118 may include both cells andcell-derived products, and may be harvested from the cell culture 104.Output cell products 118 that may be produced by the computing subsystem110 may include, but are not limited to, induced pluripotent stem cells,proteins (e.g., cytokines, antibodies, hormones), lipid particles (e.g.,exosomes), viral particles, somatic cells (including but not limited tofibroblasts, mature blood and progenitor cells, such as CD34+ cells anderythroblasts, keratinocytes, epithelial cells, including blood andurine-derived epithelial cells, Sertoli cells, endothelial cells,granulosa epithelial, neurons, pancreatic islet cells, epidermal cells,epithelial cells, hepatocytes, hair follicle cells, keratinocytes,hematopoietic cells, melanocytes, chondrocytes, lymphocytes (B and Tlymphocytes), erythrocytes, macrophages, monocytes, mononuclear cells,fibroblasts, cardiac muscle cells, other muscle cells, generally anylive somatic cells, and the combination of any of the above. The term“somatic cells,” as used herein, also includes adult stem cells.

The output cell products 118 may be measured by output cell productassays 120 in order to determine critical product parameters such asphenotype distribution, protein production, gene activation, genomicmakeup (including but not limited to genomic profiling assays such asPCR, qPCR, microarray, single-cell RNA sequencing, whole exomesequencing (WES), whole genome sequencing (WGS), karyotyping, shorttandem repeat (STR) analysis, sterility testing (testing for bacteriaand viruses)), or other phenotype analysis including but not limited tocell surface antigen or intracellular staining and immunofluorescence orflow analysis and cell viability, morphology and migration assays, orpotency assays such as self-renewal and teratoma formation assays, andgerm-layer differentiation assays. The output assay data may conveyed tothe computing subsystem 110 in order to refine predictive models (basedon image data, sensor data, information from prior cell cultureprocesses, and other information sources) for cell culture monitoringand control. Output cell product assays 120 may include, but not belimited to, viability assays, cell counting, flow cytometry,immunostained imaging assays, PCR assays (including but not limitedqPCR, ddPCR), RNA sequencing assays including single-cell RNA assays,cell differentiation assays, embryoid body formation assays, trilineagedifferentiation assays, karyotyping assays, DNA sequencing, or any otherimplementations known to persons of ordinary skill in the art.

The computing subsystem 110 is configured to gather data from a range ofsources, organizes the data in a manner that allows it to makepredictions of success/quality/functionality of the cell culture 104,and in many cases do so on a cell-by-cell, colony-by-colony, orregion-by-region basis. For example, using local cell density andproliferation rate data obtained through analysis of the time series oflabel-free images provided by the imaging subsystem 112, in conjunctionwith data regarding the input cells (in order to control forpatient-specific factors, for instance), and based on a large number ofobserved histories and corresponding cell quality data measured by theoutput cell product assays 120, the computing subsystem 110 may predictwhich regions of cells are most likely to yield superior cell products,and which regions are less likely to yield good product. In situationswhere cell media is limited or there is competition between cells forspace in the cell culture container 106, the computing subsystem 110 mayinstruct the cell editing subsystem 114 to remove the regions or evenindividual cells predicted to underperform.

Another function of the computing subsystem 110 is to use cell dataderived from imaging in conjunction with sensor data from the sensorsand controls 116 and assay data from the input cells 102 and/or theoutput cell products 118 in order to pre-emptively adjust cell cultureconditions according to cell count, proliferation rate, differentiationstatus, phenotype, or other factors in addition to real-time cell mediareadings. Using a model trained on previous iterations, the computingsubsystem 110 may adjust media conditions such as fresh media feed,media type, temperature, pH, dissolved Oxygen levels, reagent or vitaminlevels or other global cell culture properties using the controls 116.Similarly, the computing subsystem 110 may use cell data obtained fromimaging, potentially in conjunction with cell media sensor data, todetermine when the cell culture 104 is ready for harvest. Actuatorsutilized by the controls 116 may include, but are not limited to: liquidhandling robots, liquid circulation systems including valves and pumps,temperature control elements, pH controllers, gas exchange mechanisms tocontrol dissolved gases or any other implementations known to persons ofordinary skill in the art.

The computing subsystem 110 may control the cell editing subsystem 114to make edits to the cell culture 104 according to cell managementalgorithms (for example, to maintain a certain cell density, to maintaincertain exclusion areas within the cell culture container), in a timedmanner (for example, delivering gene-activating or gene-editingcompounds to cells at a specific interval), and/or as a result ofpredictions made by the computing subsystem 110 (for example, removal ofcells predicted not to yield the desired phenotype or optimal level offunction). “Editing” includes both destruction of cells and/or colonies(including inducing apoptosis, lysing, physically removing) as well asselective delivery of compounds into cells and/or regions of cells viaintracellular delivery mechanisms, or selective extraction of compoundsfrom the cells via intracellular delivery mechanisms.

The computing system 110 may include elements that perform conventionalimage processing (including but not limited to filtering, normalization,contrast enhancement, z-stack processing, thresholding, histogramtransformations, edge detection, correlations, convolutions, frequencyspace operations, blob detection, morphological operations,registration, warping, object detection, object tracking or combinationsthereof), deep learning based image processing (including but notlimited to convolutional neural networks, fully-connected neuralnetworks, semantic and instance-level segmentation, encoder-decodernetworks, multi-scale algorithms, recurrent networks, visual attentionmodels, vision transformers, generative adversarial models, U-Nets,ResU-Net, SegNet, X-Net, ENet, BoxENet, long short-term memory neuralnetworks, and combinations thereof), statistical models, patternrecognition, statistical learning (including but not limited to linearregression, non-linear regression, hierarchical regression, generalizedlinear models, logistic regression, log-linear models, non-parametricmodels), machine learning (including but not limited to decision trees,random forest, support vector machines, neural nets, deep learning,association models, sequence modeling, genetic modeling), clusteringtechniques including hierarchical and non-hierarchical clustering,supervised machine learning models, unsupervised machine learningmodels, databases (including but not limited to SQL databases and NoSQLdatabases), visualization tools for image, cell, colony, clone and otherdata, combinations of these elements, or any other implementations knownto persons of ordinary skill in the art.

The computing subsystem 110 may also include data storage for storingimage data, sensor data, the results of data analysis, and program codethat the computing subsystem 110 executes. The computing subsystem 110may also include input/output devices to allow users to view data andmonitor and control the cell culture system 100, or to transfer data inand out of the cell culture system 100. For example, the computingsubsystem 110 may include display screens, monitors,communications/interface ports, keyboards, audio systems, and the like.The computing subsystem 110 may be proximate to the other components inthe cell culture system 100 (e.g., a local computer) or may be remotefrom the other components in the cell culture system 100 (e.g., a cloudserver). In some implementations, the computing subsystem 110 may haveone or more components proximate the other components in the cellculture system 100 and some components remote from the other componentsin the cell culture system 100. The computing subsystem 110 may beconfigured to communicate with the other components in the cell culturesystem 100 utilizing a wired and/or wireless connection (e.g., Ethernetcables, optical fiber, Wi-Fi, Bluetooth), and may be configured tocommunicate with external components utilizing a wired and/or wirelessconnection. The computing subsystem 110 may have additionalfunctionality and components not disclosed herein, but would be apparentto a person of ordinary skill in the art.

The cell culture system 100 may be configured to allow extended cellculture processes to be performed within a single cell culture container106 using the cell editing subsystem 114. Because the cell editingsubsystem 114, as directed by the computing subsystem 110, canselectively remove cells from cell culture, the cell culture does notovergrow the cell culture container, and therefore does not requirefrequent transfers (“passaging”) which are stressful on cellpopulations, disrupt cell processes, introduce potential sterility andcontamination issues, and make time series tracking of cell-, region-,colony- or clone-specific behavior impossible. Thus the combination ofcontinuous monitoring via image and sensor data—enabled by thesingle-container process—may allow the computing subsystem 110 topredict the optimal regions or cells to remove in order to maintain lowenough cell density to remain in the single cell culture container 106.In the process the cell culture system 100 may also perform in-place“sorting” of cells in order to enrich the population according toreal-time measurements.

FIG. 2 is a flow chart of an example method 200 of operating a cellculture system in accordance with various implementations. The method200 may be performed by a cell culture system, such as cell culturesystem 100. In block 202, input cells are seeded into a cell culturecontainer that is fully imagable and able to support a cell culture forthe duration of the cell process. This results in a single-container,fully-imagable cell culture. The cell culture container may provide aclosed, sterile environment for cell culture processes. In block 204, acell culture process may be performed on the single-container,fully-imagable cell culture. The cell culture process may be sustainedwithin a single container for the duration of the process (as opposed totransferring, sometimes selectively, cells from container to containerto maintain property density). The cell culture process may be monitoredand controlled by a computing subsystem in the cell culture system.

In block 206, the cells may be observed with an imaging subsystem toacquire unbroken, contiguous, rich time series of cell data. In block208, the computing subsystem may analyze the cell data to develop a highfidelity predictive model for cell outcomes. The computing subsystem mayutilize the predictive model to adjust the cell culture processdynamically. For example, in block 210, the computing subsystem maycontrol a cell editing subsystem to selectively remove cells from thecell culture in order to de-densify the cell culture. The selectiveremoval, in turn, is optimally configured to improve the predictedyield, functionality, phenotype, or other properties of the output cellproduct. The method 200 may iterate through the steps of collectingimaging data, refining the predictive model, and editing the cellculture until the output cell product is produced in block 212.

In block 214, output cell product assay 214 may be performed on theoutput cell product at the end of a cell culture operation. The resultsof the assays may be used in conjunction with the time series cell datato adjust the predictive model in block 208. In some cases, the outputcell product may be harvested dynamically from the process (for example,a subset of cells may be selected and removed from the cell culture, orcell products within the media are removed from the cell culture) andthe corresponding assay results immediately fed back into the predictivemodel. In this manner, the method 200 allows for a completely automatedmethod for dynamically processing and editing cell cultures, from inputcells to output cell products. This allows for faster, more accuratecell culture processes without the time and expense of manual humanintervention, which in turn reduces the time and cost for producingoutput cell products. This approach is also easily scalable to enablelarge scale biological manufacturing.

In some implementations, preliminary process optimization and/ortraining of models is carried out using cells from non-human species,for example mouse cells, which have a segmentation clock of 2 hours vs 5hours for humans, and proliferate at a rate of 2-3× faster than humans.For example, non-human cells may be used for the development of fluidicchamber processes for reprogramming and/or differentiation more rapidlythan would otherwise be possible with slower-growing human cells. Inaddition, training of machine learning models for cell localization,pluripotency or differentiation prediction, cell colony tracking, cellcolony outcome, and combinations thereof may be performed usingnon-human cells. As another example, optimization of directed energycell culture editing strategies, patterns, algorithms, conditions, inmicrowell plate formats and/or in closed liquid chamber formats, may becarried out using non-human cells.

Multi-Focus Imaging Subsystems

In many cell culture systems, it is challenging to obtainhigh-throughput, high-content label-free cell culture images. Label-freeimaging means methods of imaging cells without labeling or altering thecells. An example of labelled imaging is fluorescent microscopy, inwhich cells are stained with fluorescent compounds that interact withcertain laser wavelengths to allow for high contrast imaging. However,labeling cells may alter and damage cells, which may lead to defects inthe output cell product. Conventional label-free imaging methods havetheir own drawbacks. For example, brightfield imaging gives littlecontrast and little information about cellular or intracellularstructures. Phase contrast imaging gives only very local, relative phaseinformation which is not consistent across cell types and densities.

In addition, maintaining focus is often an issue. To achieve steadyfocus, most cell culture imaging systems either use a step-and-imagesystem (where the XY motion, settling, and autofocus take significanttime) and/or use a low magnification/numerical aperture (NA) to achievea large focus depth, which again reduces cell data. The problem iscompounded if used in conjunction with a laser cell editing system, inwhich the laser must accurately hit cells/regions and be in focus toachieve its intended effect (e.g., destroying/removing individual cellsor regions, or temporarily permeabilizing cell membranes to allowintracellular transport of compounds).

The systems and methods disclosed herein solves multiple issues inconducting high-speed, label-free cell culture imaging by using lineardefocused (or “multi-focused”) images. Multi-focus imaging allows forcontinuous focus adjustment for imaging as well as optional laserscanning, and multi-focus imaging of cells which serves to provide datathat provides enhanced structural information regarding cells or regionsof cells. The various implementations disclosed herein allow thisfunctionality to be integrated into a continuous-motion imagingsubsystem for high-throughput imaging and/or laser editing.

Various implementations disclosed herein include an imaging subsystemthat makes multiple passes over a cell culture container to obtain imagestripes. The image stripes may be assembled into a complete picture ofthe cell culture. For example, the image may include information alongthe X, Y, and Z axes using the multi-focus capability described herein.This image may be processed and analyzed by a computing subsystem todevelop a cell editing strategy. In cases in which the cell editingsubsystem is a laser editing mechanism, another pass over the cellculture is made and the laser is used to edit cells, with themulti-focus imaging subsystem used to ensure that the edits are made atthe intended locations.

FIG. 3 include graphs illustrating how cell features may be observed atdifferent focus planes in a brightfield illuminated cell culture inaccordance with various implementations. For example, graph 302 depictsa cross-section of a single cell along the X axis, with the Z axis inthe vertical direction and representing height. Graph 302 shows a cellbody 304 containing cytoplasm and various other components, a nucleus306, and nucleoli 604. In many applications the nuclear location is usedto locate cells, but the cell body extent and shape, as well as theintracellular or nuclear components, may also give information about thecell state, phenotype, health, cell cycle, etc. For example, it is knownthat human iPSCs typically have two or more prominent nucleoli.

The shading in FIG. 3 is meant to depict the relative refractive indexof the components, with the cell body 304 being at a higher refractiveindex than the surrounding cell media, and the nucleus 306 typicallybeing at a higher refractive index than the cell body 304. It is thesedifferences in refractive index that make cells or colonies visible inlight microscopy, based on how the cellular components cause a phasedelay in light passing through them, with resulting diffraction oflight. There may also be some absorption (imaginary component of complexrefractive index) by cellular components (for example if melanin ispresent), but typically the real component of the complex refractiveindex dominates in 2D adherent cell culture imaging.

Graph 310 shows the phase delay (vertical axis) created by light passingthrough the cell structure, with illumination parallel to the Z axis.The resulting wavefront propagates and through constructive anddestructive interference creates a range of images at different Zfocuses.

Graph 312 shows an example of image intensity (vertical axis) of thecell culture at approximately the plane of the cell (i.e., Z˜0). At thisfocus level, the resulting signals are typically extremely small, andcorrespond to the smallest features in the cell and their diffractionpatterns. Typical image-based microscopy autofocus systems select thisplane because they seek a Z focus where the smallest resolvable featureshave maximum intensity (i.e., where single-pixel features are mostprominent). However, as can be seen from graph 312, the images obtainedat this plane typically contain only edge information, and can bedifficult to interpret, particularly in dense cell cultures.

Graphs 314 shows an example of the image intensities (vertical axes)obtained at a range of Z focuses (e.g., +Z₂, +Z₁, 0, −Z₁, −Z₂). As isseen in the graphs 314, as Z moves away from the “zero” or “in-focus”plane, larger structures can be resolved in the intensity images,because the phase effects of these structures cause constructive ordestructive interference as they propagate a sufficient distance. Imagesmay be sampled at both positive and negative Z levels. Even though pairsof images at the same positive and negative Z displacements may be roughinverses of one another, they may be combined in subsequent computationsto remove baseline or background effects, and also to compute both real(refractive index/phase delay) and imaginary (extinction) effects of thecell culture. Thus collecting imaging information from three dimensionsof a cell culture provides additional information that is valuable fordata analysis and cell editing decisions.

FIG. 4 is a block diagram of an example imaging subsystem 400 of a cellculture system (e.g., cell culture system 100) in accordance withvarious implementations. A cell culture surface 402 is moved relative tothe imaging subsystem 400 in a direction of motion 404. For example,this direction of motion 404 may be orthogonal to a vertical axis 416 ofthe imaging subsystem 400. The cell culture container containing thecell culture surface 402 may be translated and the imaging subsystem 400may be held still, or vice versa. Optical elements, such as objectivelens 406 and tube lens 408, may project an image of the cell culturesurface 402 onto an image sensor 410. The image sensor 410 may be anarea sensor (CMOS, CCD), or a series of linear detector arrays arrangedperpendicular to the direction of motion 404. The image sensor 410 maybe tilted along the direction of motion 404 such that the imaged planein the sample is tilted, as indicated by parallel lines 412 on aprojected tilt of the cell culture surface 402 and lines 414 on theimage sensor 410. Using this arrangement and the linear motion of theimaging subsystem 400 relative to the cell culture surface 402, eachportion of the sample is imaged at multiple Z planes as it istranslated, which is illustrated in further detail with respect to FIG.5 . With a known relative velocity, the individual (linear) Z focusimages are then realigned to form a composite multi-focus image of eachpoint in the cell culture surface 402.

FIG. 5 include graphs illustrating the imaging of a single cell using amulti-focus imaging subsystem (e.g., imaging sub-system 400) inaccordance with various implementations. The imaging subsystem maysample at three different points along the Z axis using three detectors.The graphs illustrate the imaging process along a single dimension(e.g., the X axis), but it should be understood that each detector maybe a linear detector array (e.g., linear along the Y axis orthogonal tothe figure). The detector arrays may be a single linear array, or arrayswith a number of lines, for example a 2048×16 array, with the longeraxis perpendicular to the relative motion between the cell culture andimaging subsystem. The linear detector arrays may be portions of an areasensor, as shown in FIG. 4 . However, in the simplified example shown inFIG. 5 , three discrete detectors and the corresponding signals as acell passes through the imaging volume are shown.

Graphs 502 show three timepoints as the cell passes the imagingsubsystem at a velocity v in a direction of motion 504. A single cell506 is shown moving across the imaging subsystem along the direction ofmotion 504, and a series of images along a tilted focus plane 508(tilted along the Z axis) are sampled to obtain signals that can be usedto compute cellular structural information. At a first time pointt₀−Δt₁, a first detector array 510 samples a first position 512 as thecell passes through it, with the focus adjusted to a first Z position514 (e.g., a first −Z offset). The resulting intensity signal 516 isshown as a complete trace (observed over a short time period), but issampled at high speed as the cell passes the first position 512,indicated by the vertical line. Since the first detector array 510 isimaging a plane at a significant Z offset, the signals observed by itcorrespond to diffraction from larger structures in the cell culture.

At a second time point t₀, a second detector array 518 is used to imagea second Z position 520 and produces a time-dependent signal 522 as thecell passes the second Z position 520. The signal produced at this Zposition may correspond to medium-sized structures such as the cellnucleus. At a third time point t₀+Δt₁, a third detector array 524 isused to image a third Z position 526 and produces a time-dependentsignal 528 as the cell passes the third Z position 526. The signalproduced at this Z position may correspond to small-sized structuressuch as the cell nucleoli.

Graph 530 shows how the signals generated by the detector arrays ingraphs 502 may be combined using appropriate time delays (correspondingto spatial distance along the X axis in this imaging configuration) toproduce a composite image of the cell that contains multi-scalestructural information in a single image. A relatively simple additionoperation is shown here, but more sophisticated operations such asiterative transport of intensity solutions may be employed to obtain agood prediction of phase delay through the cell and its components.

The multi-focus image generated by the imaging subsystem 400 may then beused to compute structural information on individual cells, groups ofcells, regions or colonies. This structural information includes but isnot limited to location, density, nuclear location, intracellularstructures, 3D profile, and refractive index. Data processing andanalysis may be performed in order to obtain additional information,such as estimating internal structure, phase shift, refractive indexand/or Z profile. More generally, these techniques may be used to builda quantitative phase image (QPI) of the cell culture, without the use oflaser or other interferometric hardware implementations and techniqueswith their added complexity, instability and phase-unwrappingcalculation requirements. These computational methods include but arenot limited to solving the Transport of Intensity (TIE) equation fromthe multiple focus images, which is described in Zhong, Jinshan, et al.,“Transport of Intensity phase imaging by intensity spectrum fitting ofexponentially space defocus planes,” Optics Express Vol. 22, Issue 9,pp. 10661-10674 (2014), which is incorporated by reference in itsentirety, and as described in conjunction with a range of illuminationarrangements in Zou, Chao et al., “High-resolutiontransport-of-intensity quantitative phase microscopy with annularillumination,” Nature Scientific Reports Vol. 7:7654 (2017), which isincorporated by reference in its entirety. In other implementations,deep learning models such as convolutional neural networks (CNNs) may beused to directly process the captured image data and output higher-levelpredictions about the cells, cell regions, colonies or cell culture as awhole. For example, a CNN may be used to create a virtual fluorescenceimage from the multi-focus component images generated by the multi-focusimaging subsystems disclosed herein. This may be more efficient thanfirst computing a phase image and then using this phase image as aninput to downstream models or processing.

FIG. 6 is a block diagram of another example imaging subsystem 600 in acell culture system in accordance with various implementations. A cellculture surface 602 is moved relative to the imaging subsystem 600 in adirection of motion 604. For example, this direction of motion 604 maybe orthogonal to a vertical axis of the imaging subsystem 600. The cellculture container containing the cell culture surface 602 may betranslated and the imaging subsystem 600 may be held still, or viceversa. Optical elements, such as objective lens 606, may project animage of the cell culture surface 602 onto a plurality of beam splitters608.

The beam splitters 608 may split the light from the objective lens 606into a plurality of paths, each path passing through a tube lens 610that focuses the light onto a sensor 612. The sensors 612 may be placedat varying distances from the tube lenses 610 in order to samplemultiple Z planes within the image signal. The sensors 612 may beoriented flatly along the focus plane of the tube lenses 610. Thesensors 612 may be linear detector arrays, linear detector arrays with afew elements along the short axis (for example, 2048×4), or an areasensor. Area sensors may be used in a number of modes, such as (1)full-frame mode, (2) utilizing one or more regions of interest tocorrespond with linear sections projected onto them (for higher speedoperation), or (3) in subsampling mode in which a small number of linesare sampled (for higher speed operation).

FIG. 7 is a block diagram of another example imaging subsystem 700 in acell culture system in accordance with various implementations. A cellculture surface 702 is moved relative to the imaging subsystem 700 in adirection of motion 704. For example, this direction of motion 704 maybe orthogonal to a vertical axis of the imaging subsystem 700. The cellculture container containing the cell culture surface 702 may betranslated and the imaging subsystem 700 may be held still, or viceversa. Optical elements, such as objective lens 706, may project animage of the cell culture surface 702 onto a focusing lens 708. Thefocusing lens 708 may focus light onto a slit aperture 710 which servesto isolate and filter the signal from the imaged line. A collimator lens712 captures and collimates the filtered light and projects it onto amulti-focus diffractive element 714. The multi-focus diffractive element714 may be configured to diffract the light into multiple discrete imagepaths, each with a different effective Z focus. A lens 716 images theseimage paths onto a sensor 718, which may be an area sensor or multiplelinear detector arrays. Example implementations of the multi-focusdiffractive element 714 and sensor 718 setup is described with moredetail in reference to FIGS. 8-9 . Using this configuration, multipleimages of the light signal from the cell culture are capturedsimultaneously as the imaging subsystem moves relative to the cellculture. A computing subsystem may be configured to re-compose theimages into multiple 2D images, each representing a different Z focusimage of the cell culture.

FIG. 8 is a diagram of a multi-focus diffractive element projectingmultiple Z focus plane images onto multiple detectors in accordance withvarious implementations. FIG. 8 illustrates one example implementationof the multi-focus diffractive element and sensor setup shown in FIG. 7. A cell 802 moves relative to the imaging subsystem along a directionof motion 804 with a velocity v, which may be a constant velocity insome implementations. At a certain point in time during the imaging, aline 806 along the Y axis (shown here as a single vertical slice in onedimension) is imaged. A multi-focus element 808 splits the opticalsignal along the line 806 into a plurality of beams 810, eachcorresponding to different Z focuses (i.e., different values along the Zaxis). A number of optical elements (e.g., objective, lenses, andapertures) may be disposed between the multi-focus element 808 anddetectors 812, the optical elements not shown in FIG. 8 for simplicity.A series of detectors 812, for example linear detector arrays orportions of an area sensor array, convert the optical signalscorresponding to different Z focus images into electrical signals 814.These electrical signals are combined by a computing subsystem 816(which may be similar to computing subsystem 110 in FIG. 1 ) to form arepresentation of the cell as a function of X (derived from time andvelocity), as shown in graph 818. In other implementations, theindividual images from the multiple detectors 812 may be built upseparately. Then the multiple focus images may be used as an input toCNNs or other models directly in order to predict cell, cell region,cell colony or cell culture properties such as cell locations, nuclearlocations, cell cycle, cell density, cell layer thickness, cellphenotype, cell colony information, or a variety of other properties.

FIG. 9 is a diagram of another example implementation of a multi-focusdiffractive element and a detector in accordance with variousimplementations. FIG. 9 illustrates another example implementation ofthe multi-focus diffractive element and sensor setup shown in FIG. 7 . Acell 902 moves relative to the imaging subsystem along a direction ofmotion 904 with a velocity v, which may be a constant velocity in someimplementations. At a certain point in time during the imaging, a line906 along the Y axis (shown here as a single vertical slice in onedimension) is imaged. The light signal is received by an optical element908, which is configured to produce a continuous range of Z focusesalong the imaging line 906. The effective Z focus is depicted by thecurve 910, shown here with a non-uniform focus spacing such that finerincrements of focus are captured near Z=0, and broader steps arecaptured at large +/−Z. This continuously-variable focus image isprojected onto a detector array 912.

The detector array 912 may have a large number of elements along the Yaxis (orthogonal to the figure) to sample the image line 906 as the cellculture is translated by the imaging system. The detector array 912 mayalso have a series of elements along the X axis configured to sample thedifferent Z planes as projected by the optical element 908. For example,a linear array such as the Hamamatsu S10202-16-01 CCD array (4096×128elements) may be used to image a Y-axis stripe as the sample istranslated along the X axis. The optical element 908 projects differentZ focus images across the 128-wide direction, so that as cells moveacross the image line 906 a multi-focus image of each cell is capturedand then a representation is reconstructed from this data. In someimplementations, the detector array 912 may operate in “frame mode,” inwhich the entire 4096×128 image is exposed and read out simultaneouslyat a high rate. In other implementations, the detector array 912 may beused in time-delay integration (TDI) mode, which integrates signalsalong the 128-element axis as objects translate across the X axis. In atilted-focus configuration such as the one shown in FIGS. 4-5 , theimaging subsystem may be configured to sample a range of −Z planes whereobjects diffract light to form bright areas, with the Z depth of thisbrightness dependent on the size of the phase objects. By synchronizingthe TDI transfer and integration with the motion of the cell culturerelative to the imaging subsystem, a “summed” signal across multiplefocus depths may be produced in the integrated output of the detectorarray 912. Using the example of a Hamamatsu sensor, this scheme couldproduce a phase representation of a cell culture at 100,000lines/second×4096 pixels=over 400M pixels/second.

FIG. 10A is a block diagram of an extension of the imaging subsystemshown in FIG. 7 in accordance with various implementations. Inimplementations without an auxiliary optical focus guide (e.g., theimaging subsystem 700), focus may be measured from the captured images.For example, a gradient measurement method that produces a peak signalwhen the image of the cell culture is in focus may be used. The overallsystem focus may be adjusted such that this “focus” signal is at amaximum for the central linear image capture (and then the adjacentlinear detectors capture the +Z and −Z focus images).

Imaging subsystem 1000 in FIG. 10A includes an illumination subsystemconfigured to enhance autofocus capability. In this implementation, alaser module 1002 having optics (e.g., diffractive and lenses) projectstwo lines 1004 onto the cell culture surface via a beamsplitter/combiner 1006. This light is reflected from the surface bearingthe cell culture and into the multi-focus imaging subsystem 1000. Thesensor detects the light reflected from the lines 1004, as shown ininset 1008. The lines are positioned at one or both edges of the imagedregion, and parallel to the relative motion of the imaging subsystem tothe cell culture. Inset 1008 shows an example of the laser focus guidesprojected onto a 3-linear element imaging system, each elementrepresenting focus planes at +Z, Z˜0, and −Z. The projected lines aredefocused and produce larger spots in the +/−Z plane detectors, whilethe spots at the Z˜0 detector is smaller. The imaging subsystem and/orcomputing subsystem may then use a number of control strategies by whichto adjust focus. For example, it can minimize the spot size in thecentral linear sensor (Z˜0), or also use the relative spot sizes in the+/−Z linear sensors to adjust overall focus (mechanically) in order toequalize or maintain a certain proportion between spot sizes in +/−Z.

FIG. 10B shows autofocus system output from a system utilizing a 532 nmpulsed laser for cell culture editing as well as autofocus functions. Alaser steering system projects a repeated pattern of points into thefield of view of the imaging system, and a z translator translates theobjective relative to the cell culture container. The “focus parameter”(y axis) indicates the sharpness of the projected points in the imagingsystem. Two peaks are shown, one at the external face of the wall of thecell culture vessel, another at the internal face where cells adhere.Accordingly, FIG. 10B illustrates the use of existing system componentswithin an imaging and laser cell editing system/subsystem to achieveaccurate autofocus.

FIG. 11 is a block diagram of a system 1100 that includes an imagingsubsystem combined with a cell editing subsystem in accordance withvarious implementations. The imaging subsystem may be similar to theimaging subsystem 700 shown in FIG. 7 . The cell editing subsystem maybe used to edit the cell culture and may be similar to cell editingsubsystem 114 in FIG. 1 . The cell editing subsystem shown in FIG. 11may be a laser scanning system. In this implementation, the laserscanning system raster-scans perpendicular to the direction of relativemotion as indicated by dashed line 1102, and the energy is modulatedaccording to cell editing instructions generated by a computingsubsystem.

The cell editing subsystem may include a pulsed laser 1104 thatgenerates laser pulses that are projected into an acousto-opticdeflector and modulator (AODM) 1106. The AODM 1106 modulates the pulseenergy on a per-pulse basis by deflecting some energy into a first orderbeam 1108, while allowing the zero-order beam to pass through to a beamdump 1110. By varying both the RF frequency and RF power to the AODM1106, it is possible to adjust the angle of the first order beam 1108 ona pulse-by-pulse basis. This angle may correspond to the axis of travelof the imaging subsystem relative to the cell culture. The angleadjustment by the AODM 1106 allows for a number of features, including(a) compensation of position for motion when using a resonant mirror(without this, the scan forms a “zig-zag” pattern; with thiscompensation, parallel lines are possible); (b) trimming of position tohit cells at specific points; and (c) adjusting the “lag” of the laserscanning line behind the imaging line (in some cases the scan line maybe switched to the opposite side of the imaging line, if direction ofrelative motion is reversed).

The first order beam 1108 is separated from the zero-order beam using apick-off mirror 1112, which directs it towards a rotatable mirror 1114.The rotatable mirror 1114 may be a resonant galvo mirror, a spinningpolygon mirror scanner, or any or type of rotatable mirror apparatus.The rotatable mirror 1114 allows for laser scanning perpendicular to theaxis of relative motion. The laser light is directed to the objectivevia scan optics 1116, which may include a scan lens, tube lens, and/orother optical elements. A dichroic beam combiner/splitter 1118 redirectsthe laser light into the objective and towards the cell culture. Thedichroic beam combiner/splitter 1118 is wavelength-specific and has lowloss for both the laser and imaging wavelengths, and prevents laserlight from entering the imaging path.

A computing subsystem 1120 in the system 1100, which may be similar tothe computing subsystem 110 in FIG. 1 , may be configured to control thecell editing subsystem and the imaging subsystem. The computingsubsystem 1120 may be configured to perform a number of functionsincluding but not limited to: composing a composite 3D image from themulti-focus line images acquired during travel; adjusting overall systemfocus based on the collected images; processing the composite 3D imagesto produce information about cell location, size, shape, refractiveindex, intracellular structure, density, phenotype, etc.; deciding acell editing strategy for the cell culture; during laser editing,imaging the cell culture and registering features of the cell culture orcell culture container to the previously-acquired images; and drivingthe AODM 1116 in order to deliver the desired effect to the cell cultureon a pulse-by-pulse basis, after adjusting for registration withpreviously-acquired features.

Single-Shot Fourier Ptychographic Imaging Subsystems

There are several challenges when imaging live cell cultures,particularly in the context of an automated cell culture system asdescribed herein. First, living cell cultures are generally imagedlabel-free because labelling could damage the cells, hinder cell growth,introduce contaminants, or other negative effects. Second, automated oranalytical processes built for live cell cultures usually require a highdegree of detailed information about the cells. This informationincludes, but are not limited to, nuclear locations, cell membrane andcytoplasm morphology, and intracellular and/or intranuclear structuresand configuration.

Third, there should be high throughput for imaging of live cell culturesfor several reasons, such as sensitivity to changes in environmentalconditions outside an incubator. The ability to detect small changes isimportant for large-area, high-frequency imaging for R&D, but isespecially important for clinical applications where doses are large andthere should be short time gaps between imaging, image processing,decision making, and subsequent editing or other operations on the cellculture. Lastly, the system should have the ability to spatially aligncell editing operations (e.g., cell removal, cell harvest, intracellulardelivery or other, spatial operations) accurately with the selectedcells in the live cell culture so that editing operations performedright after imaging are spatially accurate.

While certain imaging methods may be implemented in an automated cellculture system, they generally have one or more drawbacks. For example,quantitative phase imaging (QPI) has been demonstrated to provide highinformation content on cells and intracellular structures. However, theconventional way of acquiring QPI images using holography (interferenceof light passing through the sample with a reference beam) requirescomplex and expensive optical paths and are very sensitive to operatingconditions such as small changes in path length, includingnonuniformities in the coverslip, cell media, etc.

An alternative approach is Fourier ptychography (FP)—the use of multipleillumination angles on the sample, together with a conventionalobjective that gathers multiple low-resolution images corresponding tothese illumination conditions, to reconstruct high-resolution phase andamplitude images of the sample. Fourier ptychography can use low-costcomponents such as off-the-shelf LED arrays, conventional, low-NAobjectives, and CMOS imagers. A wide range of architectures have beendeveloped to implement FP imaging. However, none of the FPconfigurations described to date are suitable for very high throughputimaging of live cell cultures, which involves translating the imagerrelative to large cell culture vessel surfaces to capture and processlarge-area, contiguous imagery for subsequent visualization andautomated image processing. A description of the class of techniques andalgorithms may be found in Zhen et al., “Concept, implementations andapplications of Fourier ptychography”, Nature Physics Reviews, 3, pp.207-223 (2021), which is hereby incorporated by reference in itsentirety.

To capture multiplex images that may be used to calculate phase data forthe cell sample, while in motion relative to the sample, a “one-shot”multi-image capture architecture is required. Few “one-shot” FTconfigurations have been developed that capture multi-angle imagessimultaneously. However, these configurations are all based onillumination that is substantially normal to the sample surface, andcapture the light diffracted by the sample rather than illuminating thesample at a range of angles and observing the light that is captured bythe objective. In this configuration, the frequency response of thesystem is limited by the numerical aperture (NA) of the objective. Therequirement for a very high NA objective increases cost, reduces fieldof view (FoV) and therefore throughput, decreases working distance whichcan limit system design, and reduces the depth of focus which can makethe system sensitive to small variations in sample or containergeometry.

Thus there is a need in the art for a high-throughput imaging systemthat uses a lower-NA objective to give a large field of view, longworking distance and large depth of focus for robust, high-speedimaging. The system should also be capable of wide-angle illumination.Multiple illumination conditions from a wide range of angles, withtransmission through or reflection from the sample, measuredindependently and then combined computationally, can be used to generatea high-resolution representation of the sample even with a relativelylow-NA, wide field of view objective.

The systems and method disclosed herein include an imaging subsystem fora cell culture system that has relative low NA and wide-angleillumination. The imaging subsystem may be capable of adapting theFourier ptychography approach to high-throughput cell culturingapplications. The imaging subsystem may include a multi-angleillumination source capable of emitting multiple wavelengths, in whichthe wavelengths have distinct angular distributions. The imagingsubsystem may also include a sample illuminated by the illuminationsource, an objective collecting light from the sample, one or morewavelength-dispersive or wavelength-separating elements, one or moredetectors/sensors that detect the separated wavelengths/wavelength bandssimultaneously, and a computing subsystem to form a representation ofthe sample from the individual detector signals (corresponding todifferent illumination angles). The representation may be quantitativephase images of the sample.

The imaging subsystem may also include several other features. Forexample, in some implementations the imaging subsystem may image thesample in successive linear regions. In some implementations, theimaging subsystem may utilize linear detector arrays, or linear segmentsof an area detector, to detect each wavelength. In some implementations,the imaging subsystem may utilize linear masks at an intermediate focalplane after the objective to select light corresponding solely to alinear region. In some implementations, the sample may be moved relativeto the imaging subsystem during imaging.

FIG. 12 is a block diagram of an imaging subsystem 1200 in accordancewith various implementations. The imaging subsystem 1200 may be part ofa cell culture system, similar to imaging subsystem 112 in FIG. 1 . Theimaging subsystem 1200 may include a sample 1202. For example, thesample 1202 may be a cell culture inside a cell culture container (e.g.,cell culture container 106) in the automated cell culture system. Thesample 1202 is illuminated with a multi-wavelength light source 1204,the multiple wavelengths denoted by λ_(1-n) in FIG. 12 . Each wavelengthhas a distinct distribution of incident angles associated with it. InFIG. 12 , the angular distribution is shown in one dimension, but ingeneral there is a 2-dimensional angular distribution. The wavelengthsmay be discrete or continuous values. In the configuration shown in FIG.12 , the multi-wavelength light source 1204 illuminates the sample 1202from the opposite side of objective lens 1208. However, in someimplementations the multi-wavelength light source 1204 may be located onthe same side as the objective lens 1208 (termed an epi-illuminationconfiguration). Various examples of multi-wavelength light sources aredescribed with respect to FIGS. 15-17 .

The diffracted or reflected light 1206 exiting the sample 1202 iscaptured by the objective lens 1208. The light 1206 exiting the sample1202 has a range of angles that are a result of the illumination anglesand diffraction from the sample, and any light 1206 within the NA of theobjective lens 1208 are captured. Light exiting the objective lens 1208enters a wavelength separation subsystem 1210 that disperses orseparates the light from the sample 1202 according to wavelength. Thelight may be separated into discrete bands of wavelengths (for example,with low-pass, high-pass, bandpass filters), or there may be continuousseparation (for example, with transmissive or reflective diffractiongratings, prisms, or other high chromatic dispersion elements). Variousexamples of wavelength separation subsystems are described with respectto FIGS. 13-14 .

The spatially separated light 1212 exiting the wavelength separationsubsystem 1210 is incident on a plurality of detectors 1214 that detectthe individual wavelength bands. For light separated into discretebands, there may be a 1-to-1 correspondence between the number ofdetectors 1214 and the number of discrete bands. For light separatedinto a continuous wavelength spectrum, the resolution of the detectors1214 may determine the number of measurable wavelength bands. Thedetectors 1214 may be implemented as single-element detectors, lineardetector arrays, or 2D detector arrays.

The signals from the detectors 1214 are passed to a processing unit1216, which may include analog and/or digital computing components thatreconstructs a representation of the sample 1202 based on the light 1206from the sample 1202, as illuminated from different anglessimultaneously. The representation may be quantitative phase images ofthe sample 1202. The processing unit 1216 may combine the data capturedby the detectors 1214 simultaneously by means of an inversephase-retrieval calculation. There are several ways that the processingunit 1216 can achieve the reconstruction. In some implementations, theprocessing unit 1216 may use algorithms that reconstruct phase andamplitude iteratively by solving for a complex field (the sample 1202)that is consistent with the multiple amplitude observations by thedifferent detectors 1214 (which correspond to different illuminationangles). Alternatively, deep learning models such as convolutionalneural networks (CNNs) may be applied to reconstruct sample amplitudeand phase. These CNNs may be pre-trained on a large volume of examplesmeasured by the imaging subsystem 1200 as well as a system that producesground truth phase and amplitude (which may simply be the aboveiterative-type algorithms). The deep learning approach may significantlyreduce computational intensity and/or improve processing throughput.Finally, a deep learning approach may be used to directly outputfeatures of interest, rather than sample amplitude and phaseinformation. For example, a deep learning model may be trained toreproduce a fluorescently-labeled image of cells directly from theindependent detector observations.

The relative intensities of the wavelengths in the multi-wavelengthlight source 1204 may be adjusted according to the typical amount oflight in each wavelength band that is captured by the objective lens1208, and subsequently detected by the corresponding detectors 1214. Forexample, if high-angle illumination results in relatively low light, theillumination at the wavelength(s) corresponding to high-angleillumination may be increased, and/or low-angle illumination decreased,in order to achieve uniform intensity across the detectors 1214, whichin turn allows uniform signal-to-noise ratio and/or the same exposuretime to be used across detectors. This is of particular importance inimplementations in which a single 2D detector array with a singleexposure clock is used to image all wavelengths, and/or where the systemis continuously translating, so all detectors view the sample for thesame amount of time and therefore need to acquire signals in the sameamount of time.

The processing unit 1216 may output a signal 1218 that represents thesample 1202, the output signal 1218 including absorption and/or phaseinformation, and/or 3D structural information. For example, the sample1202 may be biological cells in a cell culture, and the output signal1218 may be a 2D representation of absorption and phase delay throughthese cells. Thus the imaging subsystem 1200 may achieve FourierPtychographic imaging of a sample in order to measure phase andamplitude components, while doing so in a “single shot” rather thanmultiple sequential illuminations and exposures, and do so with a widefrequency bandwidth but in a format that can still utilize relativelylow-NA, inexpensive objectives.

FIG. 13 is a block diagram of a wavelength separation subsystem 1300 inan imaging subsystem in accordance with various implementations. Thewavelength separation subsystem 1300 may be similar to the wavelengthseparation subsystem 1210 in FIG. 12 . Similar to FIG. 12 , sample 1302(e.g., a cell culture) is illuminated by a multi-wavelength light source1304, in which different wavelengths of light are incident on the sample1302 at different angular distributions. Light diffracted by the sample1302 (or reflected in an epi-illumination configuration) may passthrough an objective lens 1306 before entering the wavelength separationsubsystem 1300.

The wavelength separation subsystem 1300 may include a series of filters1308 that act as low-pass, high-pass, or band-pass filters that reflectone wavelength band while allowing other bands to pass through. Thefilters 1308 split the incoming light into separate streams, eachcorresponding to a different wavelength band. The light then passesthrough lenses 1310, which focus the light onto a series of detectors1312. For example, these could be 2D CMOS or CCD imaging detectors thatsimultaneously capture 2D images of the sample 1302 in each wavelengthband, which in turn each correspond to a distribution of illuminationangles. A processing unit 1314 collects the signals from the detectors1312 and combines the signals, resulting in a combined signal 1316 thatis a spatial representation of the sample 1302.

FIG. 14 is a block diagram of another wavelength separation subsystem1400 in an imaging subsystem in accordance with various implementations.The wavelength separation subsystem 1400 may be similar to thewavelength separation subsystem 1210 in FIG. 12 . Similar to FIG. 12 ,sample 1402 (e.g., a cell culture) is illuminated by a multi-wavelengthlight source 1404, in which different wavelengths of light are incidenton the sample 1402 at different angular distributions. Light diffractedby the sample 1402 (or reflected in an epi-illumination configuration)may pass through an objective lens 1406 before entering the wavelengthseparation subsystem 1400.

The wavelength separation subsystem 1400 may include a focusing lens1408 that focuses the light from the sample 1402 onto an intermediatefocal plane. A slit aperture 1410 placed in the intermediate focus planeeffectively restricts the field of view on the sample plane to a linearregion (e.g., along the X or Y axis on the sample plane). In someimplementations, a slit aperture may also be inserted between themulti-wavelength light source 1404 and the sample 1402 at anintermediate focal plane. This slit aperture may be used to restrictillumination of the sample 1402 to only an area including the field ofview to reduce any scattered light from non-imaged areas, and tominimize any illumination-related damage or biological effects.

After the light passes through the slit aperture 1410, a collimatinglens 1412 re-collimates the spatially filtered light before it reachesdispersive element 1414. The dispersive element 1414 may be a reflectivediffraction grating, transmissive diffraction grating, prism, or othercomponent that disperses the wavelength components of the optical signalin a continuous manner. The wavelength-separated (and thusangle-separated) light is then incident on focusing lens 1416 thatfocuses the light onto detector array 1418. The detector array 1418 maybe configured to detect individual wavelength and components, may becomposed of individual detectors or elements within a larger detectorarray (for example a 2D detector array). A processor 1420 receiveselectrical signals from the detector array 1418 and produces a signal1422 representative of the sample.

In some implementations, the wavelength separation subsystem 1400 may beused in a continuous-scanning imaging architecture in which the sampleand imaging/illumination system are translated relative to one anotheralong an axis of the sample plane (e.g., along the X or Y horizontalaxis of the sample plane), with one 1D linear region of the sampleimaged per readout of the detector arrays. Inset 1424 illustrates how alinear region 1426 of the sample 1402 is mapped to the detector array1418. For example, the linear region 1426 may be along the Y axis of thesample 1402. The light from the linear region 1426 is incident on the2-dimensional detector array 1418. The horizontal axis of the detectorarray 1418 is the wavelength-separated axis (marked with λ), which isthe axis along which light from the field of view is dispersed accordingto wavelength. The wavelength is in turn related to a distribution ofangles, so the signal along the horizontal axis corresponds to a measureof light scattering at different angles from the linear region 1426 ofthe sample 1402.

The vertical axis of the detector array 1418 is the spatial axis, whichcorresponds to the length of the linear region 1426 along the Y axis.The vertical axis on the detector array 1418 may be a magnification ofthe length of the linear region 1426. For example, a 0.25 mm long fieldof view of the linear region 1426 may be expanded to a length of 1.0 mmon the vertical axis of the detector array 1418 by a 4× objectivemagnification. Thus FIGS. 13-14 show several examples of wavelengthseparation of a light signal in an imaging subsystem. However, personsof ordinary skill in the art will understand that there are otherconfigurations that may achieve the same result, and thoseimplementations may be used in the imaging subsystem described herein.

FIG. 15 is a block diagram of a multi-wavelength light source 1500 in animaging subsystem in accordance with various implementations. Themulti-wavelength light source 1500 may be similar to themulti-wavelength light source 1204 in FIG. 12 . Similar to FIG. 12 ,sample 1502 (e.g., a cell culture) is illuminated by themulti-wavelength light source 1500, in which different wavelengths oflight are incident on the sample 1502 at different angulardistributions.

The multi-wavelength light source 1500 includes an assembly 1504 uponwhich the light sources 1506 are mounted. The assembly 1504 may be ahemispherical dome or a printed circuit board with multiple facets suchthat each light source 1506 illuminates the sample 1502 from a differentangle. The light sources 1506 are discrete light sources, such as lightemitting diodes (LEDs), arranged by emission wavelength across theassembly 1504 to provide illumination having a distinct relationshipbetween illumination angle and wavelength. The example shown in FIG. 15is transmissive light configuration in which light illuminates thesample 1502 from the opposite side as the objective, but it should beunderstood that similar discrete light sources can be used in reflectivemode, either side-by-side with the imaging objective, or in anepi-illumination system where these sources are transmitted through theobjective.

FIG. 16 is a block diagram of a multi-wavelength light source 1600 in animaging subsystem in accordance with various implementations. Themulti-wavelength light source 1600 may be similar to themulti-wavelength light source 1204 in FIG. 12 . Similar to FIG. 12 ,sample 1602 (e.g., a cell culture) is illuminated by themulti-wavelength light source 1600, in which different wavelengths oflight are incident on the sample 1602 at different angulardistributions. The multi-wavelength light source 1600 includes discretelight sources 1604, which have different wavelengths/wavelengthdistributions. Light from each light source 1604 passes throughcollimating lenses 1606 and enters spatial elements 1608.

The spatial elements 1608 may be configured to alter the distribution oflight coming from each light source 1604. Each light source 1604 mayhave a different spatial element 1608 associated with it so that it'sspatial shape or distribution is unique from other light sources. Thespatial elements 1608 may be simple occlusion masks, or other elementsthat shape light from a particular source with lower loss may also beused. Inset 1614 shows an example of how the spatial elements 1608 maygenerate wavelength-encoded angled illumination. In this example,collimated light from three separate light sources, each with adifferent wavelength (λ_(a), λ_(b), λ_(c)), pass through spatialelements 1608 a, 1608 b, 1608 c. Each spatial element 1608 a, 1608 b,1608 c is a mask with an opening that allow light to pass through, theopenings different and non-overlapping on each spatial element. When thelight is combined after passing through the spatial elements 1608 a,1608 b, 1608 c as shown in projection 1616, each wavelength contributionoccupies a different spatial region. The position distributionstranslate to angle distributions when focused on the sample 1602,thereby achieving wavelength encoding of illumination angle.

After passing through the spatial elements 1608, the light strikes aseries of mirrors and/or filters 1610 that combine the separate lightstreams by means of thin film interference filters or other elementsinto a single collimated optical path. This single light stream thenpasses through a condenser lens 1612 that focuses the illumination lightonto the sample 1602 with wavelength-encoded angles.

FIG. 17 is a block diagram of another multi-wavelength light source 1700in an imaging subsystem in accordance with various implementations. Themulti-wavelength light source 1700 may be similar to themulti-wavelength light source 1204 in FIG. 12 . Similar to FIG. 12 ,sample 1702 (e.g., a cell culture) is illuminated by themulti-wavelength light source 1700, in which different wavelengths oflight are incident on the sample 1702 at different angulardistributions.

The multi-wavelength light source 1700 includes a broadband light source1704, such as an LED or SLED, or incandescent light, that emitsmulti-spectrum light. A collimating lens 1706 captures the emitted lightbefore it enters a 2D spatial disperser unit 1708. The 2D spatialdisperser unit 1708 may include a number of components. These componentsmay include a cylindrical lens 1710 that focuses the entering collimatedlight into a line that enters a virtual image phase array (VIPA) 1712.The VIPA 1712 may be configured to disperse light along one axis (e.g.,Y axis respective to the sample 1702) in discrete increments. The lightthen hits diffraction grating 1714 that disperses light along the otheraxis (e.g., X axis respective to the sample 1702) depending onwavelength, thus spatially distributing the broadband light signalaccording to wavelength. The diffraction grating 1714 may be reflective,as shown in FIG. 17 , or transmissive. After being spread out in spaceand wavelength, the light may pass through collimating lens 1716,resulting in light that is collimated and spatially encoded bywavelength in two dimensions. A condenser lens 1718 focuses thewavelength-encoded light on the sample 1702. Thus FIGS. 15-17 showseveral examples of achieving multi-wavelength illumination for animaging subsystem in which the wavelength bands are angularly spread.However, persons of ordinary skill in the art will understand that thereare other configurations that may achieve the same result, and thoseimplementations may be used in the imaging subsystem described herein.

There may be additional features and variations of the imaging subsystemthat may be incorporated into the automated cell culture system. In someimplementations, there may be periodic, scheduled, and/or continuoustranslation and imaging of the sample. For example, an automated cellculture system may be configured to translate the imaging subsystemrelative to a cell culture in a continuous manner, or periodically, oraccording to a user-specified schedule, to collect time-series images ofthe cell culture.

In some implementations, the imaging subsystem may also include anautofocus (Z-tracking) system that continuously tracks the distancebetween the sample and the objective, and is able to move the sample andobjective relative to each other to maintain an optimum output signaldistance. For example, the sample and/or objective may be coupled to anactuator that is capable of moving them relative to each other, and acomputing subsystem may utilize the autofocus to determine the currentdistance between the sample and the objective, and control the actuatorsto adjust the distance. The autofocus signal that detects distance maybe produced by reflecting a light from a surface proximate to the sample(e.g., a container or microscope slide/coverslip) and the resultinglight is measured using the imaging subsystem detectors.

In some implementations, the imaging subsystem may include aregistration (e.g., XY tracking) system that measures and tracksfiducial marks or other features in the sample or sample carrier totrack location during imaging. A computing subsystem may be configuredto identify fiducials in the images and determine the location of thesample relative to other components in the cell culture system. Theregistration system may utilize the imaging subsystem detectors tocapture images of the fiducials.

In some implementations, the sample may be placed between twosubstantially flat pieces of material to minimize variations in theimaging caused by uneven surfaces not related to the sample propertiesof interest. For example, in a cell culture system the sample may be acell culture in liquid (e.g., cell media) between two surfaces of a cellgrowth or observation chamber, generally without air bubbles in themedia. In one implementation, this could be a closed cassette with flat,transparent cell culture chamber walls to enable imaging. In generalimplementations, the sample may be fixed in material between two slides,such as a histopathology sample that has been placed between two slides.

Tilt-Defocused Cell Culture Imaging and Editing Systems

Further implementations disclosed herein are directed to obtainingquantitative imaging data, label-free, with very high throughput forcell cultures. In addition, in such situations the absorption isgenerally very low, and small refractive index variations in cellular orsubcellular objects are generally the only perturbation to theilluminating wavefronts. Several approaches to obtaining quantitativephase images, or equivalents, of cell cultures have been demonstrated inthe prior art. However, almost all of these require a sequence of imagesto be obtained at a particular spatial location (for example, under aseries of lighting conditions) or with a series of z focus positions.This dramatically lowers the throughput of these imaging systems.

The implementations disclosed herein utilize an optical and imagingsubsystem that is tilted relative to the cell culture chamber and movescontinuously relative to the chamber. In combination with a novelimaging sensor configuration, the present implementations enable a broadz-stack to be obtained at very high throughput. It also combinespartially coherent illumination to make the resulting z-stack imagesuitable for transport-of-intensity equation (TIE) solutions to outputquantitative phase image (QPI) data. Further, a secondary imaging systemfor maintaining focus in real-time is described. Lastly, a laserscanning system for cell culture editing in the same optical system isalso described.

Certain implementations disclosed herein include an imaging and scanningsystem, the system including at least one light source illuminating asample (e.g., a cell culture sample) having cells grown on a growthplane of the cell culture sample, an objective capturing light from theat least one light source passing through the cell culture sample, inwhich the objective it tilted at an angle with respect to aperpendicular axis of the growth plane, and one or more sensors tomeasure the light from the objective, in which the cell culture sampleis moved relative to the imaging and scanning system such that theimaging system generates images at multiple heights along theperpendicular axis of the growth plane. This results in quantitativephase images of the sample. In some implementations, the imaging andscanning system further includes a laser pulse generated by a lasersource and incident on the cell culture sample and an acousto-opticdeflector/modular to adjust an incident angle of the laser pulserelative to the perpendicular axis of the growth plane, in which thecell culture sample is moved relative to the imaging and scanning systemsuch that the laser pulse is capable of focusing on any part of thegrowth plane.

With the z-stack image data that is provided by the presentimplementations and using formal solution and optimization using TIE, itis possible to reconstruct a quantitative phase image of the cellculture. In many applications, however, the z-stack image output may beused directly in a deep learning based model that transforms the imagedata into a predicted labeled image, based on prior training datamatching labelled images with z-stack image data.

The implementations disclosed herein have the potential to speed up theacquisition of quantitative phase and absorption imagery of cellcultures by many times. In addition, it has provisions for real-timeautofocus based on a coating placed on the cell culture vessel wall.Finally, it integrates a high-speed laser scanning system that can editcell cultures, usually based on the images obtained using the sameimaging system. Thus it provides a novel, highly-compact, integrated,high-capacity system for monitoring and controlling cell cultures andprocesses.

FIG. 18 is a diagram of a tilt-defocused cell culture imaging andediting system 1800 in accordance with various implementations. Thesystem 1800 may be part of a cell culture system (e.g., cell culturesystem 100) and may include an imaging subsystem (e.g., cell imagingsubsystem 112) and an editing subsystem (e.g., cell editing subsystem114). The imaging subsystem of the system 1800 may include a primarylight source 1802. For example, the primary light source 1802 may be alight-emitting diode (LED) that emits light collimated by a collimatinglens 1804. In some implementations, the primary light source 1802 mayhave a narrow wavelength bandwidth. In other implementations, it isdesirable to further narrow the wavelength band to achievepartially-coherent illumination on the sample. In such cases, a thinfilm interference filter (e.g., bandpass filter) 1806 may be used tofurther narrow the primary illumination wavelength band. For example,the primary light source 1802 may be an LED emitting at 625 nm, with afull-width half-max (FWHM) bandwidth of 17 nm, and the thin filminterference filter 1806 may be a bandpass filter with a FWHM of 10 nmthat further reduces the wavelength range.

Continuing the example, a secondary light source 1808 may also be used,collimated by lens 1810 and partially reflected by a polarization beamsplitter (PBS) 1812. The function of the PBS 1812 is to relay (byreflection, in this case) primarily light in one linear polarizationdirection. In this example, the secondary light source 1808 is polarizedto better separate it from laser illumination at a downstream imagesensor. The secondary light source 1808 is at a different wavelengththan the primary light source 1802, and in some implementations atroughly the same wavelength as the laser source. For example, when thelaser source is a 532 nm pulsed laser, the secondary illumination fromthe secondary light source 1808 may be provided by an LED with a peakemission in the 525-535 nm range. The light reflected by the PBS 1812 isthen reflected by a dichroic filter 1814 which allows the primary lightto pass through, and reflects the secondary wavelength from thesecondary light source 1808 and combine them into a single optical path.In some implementations, the laser source has a wavelength of at leastabout 400 nm, 450 nm, or 500 nm up to about 525 nm, 550 nm, 575 nm, 600nm, or 650 nm. In some implementations, the laser source has awavelength of about 400 nm to about 650 nm, about 450 nm to about 600nm, or about 500 nm to about 550 nm. In some implementations, the lasersource has a wavelength of about 532 nm. In some implementations, thelaser source has a wavelength of at least about 900 nm, 950 nm, 1000 nm,or 1050 nm up to about 1100 nm, 1150 nm, or about 1200 nm. In someimplementations, the laser source has a wavelength of about 1064 nm.

A focusing lens 1816 then focuses all illuminating light to an imageplane where it is spatially filtered by an aperture 1818. The aperture1818 increases the spatial coherence of the illumination source(s) forthe purpose of illuminating a sample with partially coherent light. Afold mirror 1820 relays the light to a condenser assembly 1822, whichincludes optics to illuminate a sample plane with substantially a planewave of partially-coherent light. The condenser assembly 1822 may alsoinclude a condenser aperture (shown in black) to limit the illuminationfield on the sample.

The sample 1824, which in this example may be a cell culture adherent tothe upper wall of a liquid-filled cell culture chamber, is shown in FIG.18 in cross-section with two chamber walls above and below aliquid-filled cavity. The walls are both made of transparent material,for example glass or optical-grade polymer. The upper wall may be coatedwith a laser-absorptive coating and biocompatible coatings or matricessuitable for supporting adherent or semi-adherent cell culture. Theillumination light passes through the chamber and the cell culture ofthe sample 1824 and is collected with a microscope objective 1826. Theobjective 1826 may be, for example, a 10× magnification, 0.3 numericalaperture (NA) objective. In this example, the distance between theobjective 1826 and the sample 1824 is controlled via a high-speedactuator (such as a piezo-electric actuator) 1828 to control focus asthe optical system moves relative to the sample 1824, or to account forsample-to-sample mechanical variations.

After being collected by the objective 1826, light from the primarylight source 1802 is separated using a dichroic filter 1830 and focusedvia a tube lens 1832 onto a primary image sensor 1834. The primary imagesensor 1834 captures an image of the tilt-focused image plane thatz-samples the cell culture in the sample 1824 across the field of view.Secondary illumination wavelength light passes through the dichroicfilter 1830 and is separated from the laser path using a PBS 1836, inwhich the PBS 1836 is oriented to reflect light matching the secondarysource 1808 and the secondary source PBS 1812. This light is focused bya tube lens 1838 onto secondary image sensor 1840. The secondary imagesensor 1840 is used to sense Z focus position and XY spatial position.It may do so by directly imaging the laser illumination on thelaser-absorbing film within the cell culture chamber or, as in thisexample, by imaging the laser-absorbing film as it is trans-illuminatedby the secondary light source 1808. The laser-absorbing film absorbs atthis secondary wavelength, and by pre-encoding the laser-absorbing filmwith small, ablated markers, focus point as well as XY position may betracked efficiently as the sample moves through the field of view of theoptical subsystem.

The cell editing subsystem of the system 1800 may include laser pulses,which are supplied to the system 1800 from a pulsed laser source via anoptical fiber connection 1842. The light is collimated using a fibercollimator 1844 and enters an acousto-optic deflector/modulator (AODM)1846. The AODM 1846 passes a zero-order beam 1848 directly through,where it is picked off by a pick mirror 1850 and relayed to aphotodetector 1852. The photodetector 1852 serves to measure baselinelaser pulse energy being delivered to the optical subsystem (forexample, to calibrate for changes over time or upon re-connection of afiber). Additionally, in cases in which the central pulsed laser is runat a consistent pulse rate, the photodetector 1852 may be used toacquire the laser pulse signal timing and synchronize the opticalscanning subsystem to the laser pulse timing. This obviates the need fora separate electronic synchronization system and wiring.

Based on this timing, for each laser pulse, a driver of the AODM 1846sets an RF power to deflect a certain percentage of the incoming pulseinto a first-order beam 1854, based on scanning instructions from acomputing subsystem. Additionally, the AODM driver may vary the RFfrequency slightly to change the angle of the first-order beam 1854.This allows the AODM 1846 to make adjustments to the beam angle in the“x” direction on the sample plane, for example to achieve anevenly-spaced grid of hits on the sample plane during resonant scanningand x-axis motion, or to shift the scan line (generally along they-axis) slightly along the x-axis in order to ensure best focus on thelaser absorbing film. The AODM 1846, in summary, controls pulse energyas well as pulse placement on the sample 1824 along the x-axis, on apulse-by-pulse basis. The pulse rate of the laser source in the systemmay be ≥100 kHz, preferably ≥500 kHz or even ≥1 MHz. In someimplementations, the pulse rate of the laser source in the system is atleast about 100 kHz, 200 kHz, 300 kHz, 400 kHz, 500 kHz, 600 kHz, 700kHz, 800 kHz, 900 kHz, or 1 MHz.

A scanning mirror 1856 is used to scan the laser across the sample 1824along substantially the “y” axis, in other words perpendicular to therelative motion between the optical system and sample 1824 (the scanningmirror 1856 is depicted schematically only with an axis perpendicular tothe plane of the figure). The scanning system may include a resonantgalvanometric or electrostatically-driven mirror, or alternatively mayinclude a polygonal rotating mirror. In other cases the scanning in they direction may be achieved by use of another acousto-optic deflector. Ascan lens 1858 and a tube lens 1860 are used to relay the laser beam tothe objective 1826 through a fold mirror 1862. The laser pulses arefocused onto the laser absorbing film of the sample 1824 by theobjective 1826, and the beam is scanned in the “y” direction with theresonant scanning/polygon scanner, and relative “x” position iscontrolled at a short timescale using the AODM 1846 RF frequency.

The system 1800 may be translated relative to the sample 1824 asindicated by arrow 1864. This may be achieved by physically moving thesample 1824, or by an optical subsystem assembly that moves around astationary sample holder. As the relative motion occurs, a primaryimager samples multiple focus planes of the sample 1824. A secondaryimager images the laser absorbing film and uses encoding markings on thefilm to calculate XY position in real time, as well as to calculatewhere the tilted focal plane intersects the laser absorbing film(“z=0”). This allows a control system to make adjustments to theobjective height to keep this location at a particular point relative tothe field of view. Likewise, for laser scanning and editing, the system1800 traverses the sample 1824 and keeps it at a constant focus. Thelaser system scans the laser-absorbing film with a raster-scan patternof points, in which the individual laser pulse powers (and to a smallextent, relative×position) are controlled via the AODM 1846, asinstructed by a computing subsystem (e.g., computing subsystem 110) thatis acting to edit the cell culture by lysing cells or initiatingintracellular delivery of compounds into the cells.

FIG. 19 is a cross-section of a cell culture chamber 1900 duringtilt-defocused imaging and/or laser scanning in accordance with variousimplementations. A liquid cell media-filled cavity 1902 is bounded bywalls, including the upper wall 1904 of the cell culture chamber 1900.In this example configuration, the cell culture chamber 1900 supports aninverted adherent cell culture 1906 on the surface of the upper wall1904. The cell-supporting surface of the upper wall 1904 is coated witha thin laser-absorbing layer 1908 which serves to absorb laser pulsesand convert a portion of the absorbed energy into mechanical energy inthe form of explosive microbubbles, for the purpose of lysing cells,removing cell debris, or enabling intracellular delivery of compoundsinto cells.

In this implementation, the laser absorbing layer 1908 is patterned (byablation of layer material) with very small fiducial markings 1910.Ideally these fiducial markings 1910 are smaller than the pulsed laserspot size so they do not interfere with the formation of microbubbles bythe laser, but large enough to be imaged by an imager. In someimplementations, the laser absorbing layer 1908 absorbs preferentiallyin the wavelength band of the pulsed laser, and absorbs less in thewavelength band of a primary light source of the imaging subsystem. Itcan therefore be illuminated with the secondary light source, which isin the laser wavelength band, and imaged with a secondary imager toclearly resolve these fiducial markings 1910. The fiducial markings 1910do not appear, or appear only very faintly, in the primary imager data.

The focal plane 1912 of a tilted objective is tilted relative to thecell-bearing surface and cell culture 1906. As a result, as the opticalassembly moves relative to the sample, a series of Z-height specificimages of each location (denoted by z-heights 1914) may be captured insequence by the primary imager and secondary imager. Additionally, theobjective focuses a pulsed laser light 1916 onto the laser absorbinglayer 1908. As shown here, the Z focus of the laser may be adjusted tobe slightly different from the image focal plane, such that the laserscan line does not interfere with the secondary transmission imaging atthe Z=0 point. The laser is scanned along the Y axis (perpendicular tothe plane of the figure), and may have its “x” position tuned by an AODMin response to rapid Z focus changes (since “y” position corresponds to“z” focus).

FIGS. 20A-C are imaging field views of a tilt-defocused cell cultureimaging and editing system in accordance with various implementations.FIG. 20A illustrates an effective field of view of a primary imager 2002of the tilt-defocused cell culture imaging and editing system, as wellas lines that are imaged as the imaging system moves relative to thesample. The primary imager 2002 may be a CMOS image sensor, and isoriented such that its “lines” are oriented along the sample field ofview y-axis. An example of a CMOS image sensor that may be used in thepresent implementations is the AMS/CMOSIS CMV4000 4.2-megapixel CMOSimager with global shutter. The primary imager 2002 may run at 180frames per second at full resolution, but can run at significantlyhigher frame rate if fewer rows are read out. For example, if theobjective is tilted such that the z height differential across the fieldof view 2002 along the x-axis (corresponding to “−z” to “+z”) is 50microns, and the minimum z-slice spacing in the resulting output volumeis 2.5 microns, a total of 21 rows in the imager may be used, and animaging rate of ˜8650 frames per second may be achieved, meaning thatover 4 complete fields of view (2048×2048 pixels) can be captured persecond, with 21 z slices each. An example (schematic) arrangement ofthis sparse row reading is indicated by lines 2004.

FIG. 20B illustrates a field of view of a secondary imager 2006 of thetilt-defocused cell culture imaging and editing system. The secondaryimager 2006 may be of the same type as the primary imager 2002. As withthe primary imager 2002, it may utilize only a subset of rows, but in adifferent configuration, namely more densely-spaced rows 2008 around thetarget location within the field of view of Z=0, at which the focalplane intersects the laser absorption film. By observing small features(e.g., fiducial markings) in the laser film as they pass through thisnarrow X/Z range, and the focus or sharpness level of the features, acomputing subsystem (e.g., computing subsystem 110) receiving the imagedata may compute where the optimal focus is along the x direction. Acontrol system may shift the objective according to this output to keepthe optimal focus within a small X range such that the primary imager2002 is always obtaining the same x stack relative to the laserabsorption film. In addition, high-frequency adjustments may be madeduring laser scanning by the use of a AODF to offset the laser scanalong the x (and therefore z) direction.

A built-in cell processing laser, in conjunction with the imagingsystem/subsystem, can achieve autofocus on the sample by imaginglines/points projected using the laser and laser steering system ontothe cell culture container, and measuring the sharpness of these linesor points. In this manner a very compact imaging and laser editingsystem can be built, without the need for additional autofocussubsystems.

FIG. 20C illustrates a field of view 2010 of the secondary imager withthe laser scan line superimposed. The laser scan line is along they-axis, perpendicular to the motion of the optical assembly relative tothe sample. The laser scan line 2012 may be bi-directional (in the caseof a resonant scanner) or unidirectional (in the case of a polygonmirror scanner), or random-access (in the case of an acousto-opticdeflector being used for y-axis control). As described herein, the AODMmay be used to adjust the x-position of the scan line 2012 on apoint-by-point basis. In some implementations, the scan points may beadjusted to coincide with the secondary imaging zone (where the imagingis focused on the laser absorption film) to directly observe the laserhits on the laser absorption surface. This may be used as another methodto gauge z focus in real time.

The systems and methods for imaging subsystems described with respect toFIGS. 3-20C have several common features or common permutations, andelements of each implementation may be combined with each other, and maybe each be combined with a cell editing subsystem (e.g., a laser editingsystem) in a number of ways. For example, each of the imaging approachesdescribed above (multi-focus, tilt-defocused, and single-shot Fourierptychographic) are methods of retrieving quantitative phase imaging(QPI) without lasers or other interferometric setups, which add noiseand complexity. In another example, the multi-focus and tilt-defocusedapproaches may be combined with the one-shot multi-angle illuminationapproach as described in the single-shot Fourier ptychographicimplementations. In another example, each of the imaging approachesdescribed above (multi-focus, tilt-defocused, and single-shot Fourierptychographic) may be combined with a laser scanning system as describedwith respect to FIG. 18 , and in some implementations the imagingsubsystem and the laser scanning system may share a common objective.The systems and methods disclosed herein also include other permutationsof the imaging approaches disclosed herein, as understood by a person ofordinary skill in the art.

Clonally Reprogrammed iPSCs

Induced pluripotent stem cells (iPSCs) have the potential torevolutionize regenerative medicine. Their capacity for self-renewal,ability to differentiate into any cell type in the body, and ability tobe manufactured from small volumes of patient tissue samples make themthe ideal starting material for personalized cell and tissue therapies.The same genetic plasticity that allows for these cells to be used tomake biologics also makes the cell vulnerable to selective pressure andcan potentially put the product and process at risk when changes aremade.

However, there are several hurdles to creating cost-effective, safe, andefficient hiPSC-derived cell therapies. Creation of a master cell bank(MCB) of hiPSCs with current protocols is extremely labor- andtime-intensive (up to 4 months), with estimates for the cost ofgenerating a clinical-grade iPSC line going as high as US $1.2M. Amajority of these costs include labor and quality control (QC) measuresrequired for ensuring the safety and efficacy of the end product. Anymethods aimed to reduce the cost involved in these would significantlyhelp enable cost-effective manufacturing of hiPSC-derived cell therapyproducts.

One factor to the low numbers of hiPSC-lines passing the QC assays isthe heterogeneous nature of the iPSC culture. There is variability bothwithin and across iPSC lines, in terms of differentiation potential,tumorigenicity, epigenetic profile, and other parameters. The exactreason behind this remains unclear, and could be related to differencesin source material, protocols, or operator technique. Nevertheless, thisindicates a need for more standardization and automation across iPSCmanufacturing and characterization techniques, which can help minimizethe heterogeneity within the MCB and allow for well-controlled processescapable of consistent manufacturing of a product. When cell banks arenonclonal, every potential change made to the upstream process (rawmaterials, process parameters, manufacturing site, etc.) may putselective pressure on the cultures, which may result in changes to themanufacturing process or the final product. Clonality is a crucial stepin stable cell line development (CLD) for biotherapeutic workflows andit is closely monitored by government regulators. If clonality is notsufficiently evidenced, regulatory bodies such as the US Food and DrugAdministration (FDA) and the European Medicines Agency (EMA) willrequire additional manufacturing controls, increasing the cost ofclinical trials and delaying drugs from reaching patients.

There are a number of iPSC reprogramming methods, including genomeintegration, non-genome integration, minicircle vectors, the Sendaiprotocol, mRNA, self-replicating RNA, CRISPR activators, and recombinantproteins. Each of these are summarized herein.

Genome integrating methods: one of the most commonly used methods forreprogramming is the integration of the reprogramming factors into thegenome by lentiviral or retroviral transduction. This method is highlyefficient but poses the threat of generating permanent randomintegrations of exogenous genes into the genome that can potentiallyhave oncogenic potential and are therefore less suitable for use intherapeutic approaches.

Non-genome integrating methods: non-genome integrating methods(footprint-free) include a number of methods to exogenously expressreprogramming factors and RNA components, from either episomal DNAvectors, RNA viruses, or messenger RNAs (mRNAs). Among integration-freemethods, the episomal method is a technically simple, fast, convenient,and reproducible approach for generating iPSCs. However, episomalvectors have low reprogramming efficiency in comparison with viralvectors. Furthermore, in many studies that used the episomal system, thetranscription factors were delivered individually by nucleofection.However, due to differences in vector uptake by nucleofection, geneexpression levels between cells are highly variable.

Minicircle vectors: minicircles are DNA vectors with eliminatedbacterial backbones and transcription units commonly used in episomalplasmids. Therefore, they have a relatively small size compared to othercommercial vectors. The small size and the ability to avoid immunereactions leads to the high expression of the foreign gene, both invitro and in vivo. Minicircles also show potential in pre-clinical genetherapy research and proof-of-concept studies combining minicirclevectors and stem cells suggest a potential regenerative tool forclinical applications.

Sendai: the Sendai virus is a single chain RNA virus that does notintegrate into the host genome or alter the genetic information of thehost cells. The virus remains in the cytoplasm and is therefore dilutedout of the host cells after approximately ten passages after virusinfection. Sendai virus can infect a wide range of cell types inproliferative and quiescent states with high transduction efficiency.Expression of transgenes delivered by Sendai virus is detectable asearly as 6-10 hours after transduction, with maximum expression detectedmore than 24 hours after transduction.

Sendai-based reprogramming vectors have been used to successfullyreprogram neonatal and adult fibroblasts as well as blood cells withhigh efficiency.

CRISPR activation (CRISPRa): CRISPRa uses a catalytically inactivatedCRISPR-Cas9 system (dCas9) fused to a transactivator domain fortranscriptional activation of endogenous genes without editing DNA. Highefficiency, multiplexed, fibroblast CRISPRa reprogramming has recentlybeen reported with improved fidelity. Activation of reprogramming geneendogenous promoters with CRISPRa improves the quality of humanpluripotent reprogramming.

mRNA: expression of reprogramming factors using mRNA provides anothermethod to make transgene-free iPSCs. It was shown that in vitrotranscribed mRNAs were able to efficiently express reprogramming factorswhen transfected into human fibroblasts. Although reprogramming factormRNAs are commercially available, this method suffers from thelimitations that it is labor-intensive, requires daily transfection ofmRNA for 7 successive days, and there are no successful reportsregarding the reprogramming of blood cells. However, despite the greatadvances in the development of synthetic mRNA-based reprogrammingapproaches, one of the main obstacles of this method is still theinduction of an innate immune response following multiple daily mRNAtransfections, resulting in increased cellular stress and severecytotoxicity.

Self-replicating mRNA (srRNA): an alternative to mRNA-basedreprogramming is the use of srRNA. Structurally, srRNA mimics itssynthetic mRNA counterpart, and contains the coding sequences of the“Yamanaka” transcription factors Oct4, Klf4, Sox2, and cMyc, and fournonstructural proteins enabling its replication. The application ofsrRNA enables an extended duration of protein expression without theneed of multiple daily transfections to maintain the protein expressionrequired to reprogram cells.

Recombinant proteins: protein-based hiPS technology offers a new andpotentially safe method for generating patient-specific stem cells thatdoes not require the destruction of ex utero embryos. This systemcompletely eliminates genome manipulation and DNA transfection,resulting in human iPS cells suitable for drug discovery, diseasemodeling, and future clinical translation. However, the generation ofp-hiPS cells is very slow and inefficient, and requires furtheroptimization. In particular, the whole protein extracts that are usedlimits the concentrations of factors delivered into the target cells,thus suggesting that p-hiPS cells may be more efficiently generatedusing purified reprogramming proteins.

Due to the plastic nature of somatic cells upon reprogramming, hiPSCscan be created from several cell sources that may be classified into twogroups: adherent and suspension. Each comes with different sets ofchallenges and benefits, which are discussed herein.

Fibroblasts and other adherent cells: Fibroblasts are the most commonlyused primary somatic cell type for the generation of iPSCs. Variouscharacteristics of fibroblasts supported their utilization for thegroundbreaking experiments of iPSC generation. One major advantage isthe high availability of fibroblasts which can be easily isolated fromskin biopsies. Furthermore, their cultivation, propagation, andcryoconservation properties are uncomplicated with respect tonutritional requirements and viability in culture. However, the requiredskin biopsy remains an invasive approach, representing a major drawbackfor using fibroblasts as the starting material. Additionally, it hasbeen shown that especially skin fibroblasts accumulate mutations duringthe person's lifetime that might negatively affect the outcome of thereprogramming process. Other adherent cell types used for reprogramminginclude keratinocytes from hair follicles and skin biopsies, epithelialcells derived from urine and blood, synovial cells, and beta isletcells. The compatibility of all the potential somatic cell types withthe existing and emerging reprogramming methods will need to beevaluated by persons of skill in the art.

Suspension cells: CD34+ blood stem cells and erythroblasts purified fromperipheral blood mononucleated cells (PBMCs) are one of the most studiedcell types as a starting material for reprogramming. This is mainly dueto their easy harvest via blood withdrawal, and the low number ofmutations these cells accumulate over the lifetime that might negativelyaffect the outcome. All reprogramming methods minus mRNA electroporationhave been successfully used to reprogram these cell types.

Assurance of clonality is part of the overall control strategy forcell-based products. It improves the consistency of the process anddirectly affects the quality and safety of the products. However, forcell-based biologics entering clinical phase, there exists no singleregulatory document that explicitly states that the cell banks should bemonoclonal, mainly reflecting the inability of the current technologiesto ensure monoclonality. However, starting with a monoclonal populationwould maximize the potential to optimize the manufacturing process byreducing variables associated with heterogeneous cell behavior withinthe culture.

The sole method currently able to distinguish a monoclonal populationfrom a polyclonal one in an already established cell line is FluorescentIn Situ Hybridization (FISH). It relies on random monoallelic expressionof genes (so-called allelic exclusion), in which a subset of human genesare normally expressed at a single allele in a fixed fraction of cellswithin a tissue, independent of the parental origin of the allele. It ishypothesized that application of FISH to assess the allelic expressionpatterns among one or more of these genes should be able to distinguisha monoclonal population of cells from a polyclonal on. However, althoughfairly successful in determining the clonality of B and T-cell lines dueto the specific recombination events occurring in them, applying FISH toother cell types (such as hiPSCs) that do not naturally undergo geneticrecombination has proven to be technically challenging and incompatiblewith reliable high-throughput analysis of samples. Therefore, due tolack of biological assays, the current methods to assess clonality ofhiPSCs rely on image-based assurance of single-cell origin of theculture and/or statistical methods to reduce the probability of cellsoriginating from multiple cells within the culture. Several clonalitystrategies are described herein.

Single-cell plating (limiting dilution): in order to create a moreuniform, homogeneous population of hiPSCs, many laboratories opt forclonal derivation of the cell lines. By plating a single hiPSC pergrowth area for expansion, the resulting product is a clonal populationof cells where each cell is genetically and phenotypically more similarto the other cells in the same culture than in hiPSC-cultures withnon-clonal origin. Single-cell plating can be done with several methodsfrom limiting dilution to cell sorting. Single-cell origin of theculture is specifically critical for gene-edited hiPSCs where each cellin the culture must carry the edited version of the gene. Unfortunately,the process of creating clonal cultures from single cells poses asignificant challenge to the cells that require contact with neighboringcells to survive. Due to this, the survival rate of hiPSCs aftersingle-cell plating is very low, and the cells that do manage toproliferate and expand often have acquired mutations beneficial forsingle-cell survival, but that result in failure during the end QC.

Low-density plating (repeated colony picking): to avoid having to platehiPSCs at single cells, many laboratories and publications rely onstatistical probability modeling and derive “clonal” populations byplating hiPSCs at low density and picking and replating pieces from asingle colony several times either manually or with technologies such asClonePix. This has been shown to result in highly homogenous hiPSCcultures, yet does not provide an absolute proof of clonality. This ismainly due to the probability of plated cells to reside within 150 μmdistance from each other, which has been shown to cause cells to migrateand form a polyclonal colony.

Clonality assays, currently, there are no assays to address theclonality of an existing hiPSC-culture. To ensure absolute clonalorigin, imaging-based techniques are suggested by the FDA to track thesingle cell during the expansion and MCB creation.

One of the quality aspects required from hiPSC-derived cell therapyproducts is the assurance of complete elimination of the reprogrammingmaterial. For integrating methods this requires the use of excisablegene cassettes (e.g., Cre-lox system) engineered into the viral vectorsencoding reprogramming factors. Upon activation, an exogenous enzyme(e.g., Cre-recombinase) cuts the DNA around the insertion site andremoves the cassette containing the reprogramming factor. After this thecells' own DNA repair systems repair the remaining cut in the genome andthe cell is considered “safe” and ready for downstream applications,including cell therapies. To ensure the complete excision of thecassette, sequencing of the cell population is required.

For non-integrating reprogramming methods, it suffices to prove that theDNA, mRNA, or viral vector (e.g., Sendai) is no longer detected by qPCR.The mechanism of DNA elimination in the episomal and microcircle methodsrely on cell-proliferation-based dilution of reprogramming plasmid inthe progeny of cells. Additionally, the elimination is dependent on thetype of origin of replication used to drive the replication of theseplasmids and directly affects how quickly they will be diluted below thethreshold of detection.

The time for complete elimination of DNA-based non-integratingreprogramming materials varies significantly between methods and clonesand can take anywhere between 40-120 days, significantly slowing downthe manufacturing process. Any methods allowing for a faster and moreconsistent elimination of the reprogramming methods would allow for morecost-effective and safe manufacturing cell therapies. Using mRNA-basedreprogramming has the major advantage of producing footprint-free hiPSCsmuch faster than other methods. Synthetic mRNA is commonly degradedwithin 48 hours after its entry into the cell. However, due to its rapiddegradation, up to 14 rounds of consecutive transfections is necessaryto retain sufficient level of protein expression to reprogram cells.Therefore, synthetic mRNA-based reprogramming is better suitable forreprogramming hardy cell types, such as fibroblasts and epithelialcells, instead of, for example, blood stem cells sensitive to multiplerounds of transfection. To overcome the challenge of multi-roundtransfections and yet produce a foot-print free hiPSC line in under 40days, a novel approach of srRNAs may be used. These synthetic mRNAs havean additional genetic element in their structure that allows them toreplicate once inside mammalian cells. Depending on the type of thisreplicative element, srRNAs can remain in the cells up to 30 days afterwhich they are rapidly removed by the cells' type I interferon activityafter the withdrawal of interferon suppressing factor B18R.

All the above mentioned non-integrating methods have been shown tosuccessfully reprogram somatic cells into hiPSCs. However, the highvariability between clones derived using these methods is hinderingtheir translation into commercial production. One of the greatestcontributors to this variability is the initial reprogramming cargo loadbeing introduced into the cell. There is currently no way to control theload of DNA, RNA, or protein that is delivered into each cell in theculture upon transfection. This depends on several factors such as cellcycle stage, metabolic activity, and cell surface area of the cellsbeing transfected. However, the amount of cargo entering the cells candirectly affect several aspects of the reprogramming process, includingreprogramming efficiency and elimination speed of exogenous material andthus the manufacturing time. Indeed, partially due to these factorssignificant variation between clones is often observed, resulting inhighly heterogeneous non-clonal culture of hiPSCs. The ability to useimage-guided algorithms to track and analyze single cells and ensureclonality during the reprogramming and expansion process can provide apowerful tool to distinguish between fully vs partially reprogrammedclones. Especially when combined with qPCR-based quantification of theremaining reprogramming material in each clone during the early days ofreprogramming, a cell culture system for growing hiPSCs may providegreat insights into selecting the best clones for acceleratedmanufacturing of safe hiPSCs.

In summary, the problems facing quick and relatively inexpensive massreprogramming of iPSCs include low yields and low consistency ofhigh-quality iPSC clones. This is exacerbated by an inability to observebehavior during reprogramming vs outcomes, inconsistent handling of thecells, and frequent passaging that causes variable effects on cells. Inaddition, it is difficult to ensure clonality on an iPSC cell culturesuch that monoclonal iPSC output cell products can be reliablymanufactured. Low fidelity of QC results and/or high QC volumes/costs,in addition to inconsistent behavior during reprogramming observation,further make consistent monoclonality a challenge.

The systems and methods disclosed herein provide a reliable, automatedprocess for monoclonal reprogramming of iPSCs, and hiPSCs in particular.The cell culture system disclosed herein (e.g., cell culture system 100)may be used to produce iPSCs that are the result of a true clonalreprogramming process, in which a single iPS candidate cell or cellcolony is isolated using a cell removal mechanism (e.g., cell editingsubsystem 114) that acts on the other cells, and confirmed by imaging.The colony/colonies resulting from proliferation of this single cell areisolated from colonies proliferating from other cells, by use of a cellremoval mechanism that acts on potentially clone cross-contaminatingcells, the removal coordinated and confirmed by imaging and imageanalysis. The colony/colonies of a single starting cell are thenisolated to form the final clonal output cell product. The entire cellculture process may be conducted in a closed system, such as a closedcassette system. The cell culture container does not need to be openedor otherwise exposed to the external environment for media exchange,imaging, cell editing, and other cell culture process operations. Thusthe cell culture system herein may be configured to grow monoclonal cellcolonies (e.g., iPSC colonies) in a closed system.

In some implementations, the isolation of a single clone from multipleclonal colonies is achieved by a cell removal mechanism that acts on theother colonies, the removal coordinated and confirmed by imaging andimage analysis. In some implementations, the cell removal mechanismincludes at least a pulsed laser system. In some implementations, theentire process up to the output cell product is performed within asingle cell culture container. In some implementations, the cells arereprogrammed in a sealed microfluidic environment, such as a closedcassette system.

The cell culture system disclosed herein provides a number of advantagesover the prior art for monoclonal reprogramming of iPSCs. For example,the cell culture system may be used to track reprogrammed cells at asingle-cell level, and a precision laser system may be used to removeany unwanted cells in the cell culture. Unwanted cells can be any cellsanalyzed and predicted by the image-based algorithms during any stage ofthe reprogramming and expansion stages that, according to thepredictions, would not pass the QC or manufacturing requirements at theend of the manufacturing process. QC requirements focus on ensuring thesafety and potency of the output cell product and are determined by theregulatory bodies. Manufacturing requirements are specific for the cellculture system and aim to reduce the cost and manufacturing time of theproduct, and may include but are not limited to eliminating cells thatdivide too slowly, cells that have high reprogramming cargo load, andmigrating, hard to track cells.

The cell culture system is also agnostic to the starting material. Thecell culture system may be configured to reprogram fibroblasts or otheradherent cells such as keratinocytes, epithelial cells or synovialcells, independent of the reprogramming method. The system's image-basedalgorithms can be used to distinguish fibroblasts from newlyreprogrammed cells based on an array of phenotypic features specific topluripotent stem cells, including but not limited to, cell morphology,cell proliferation rate, chromatin condensation, nucleus to cytosolratio and cell migration patterns. The cell editing subsystem of thecell culture system may then be used to remove unwanted adherent cells.

When the cell culture system disclosed herein is used to reprogramsuspension cells, such as CD34+ stem cells or erythroblasts, the numberof cells adhering to the cell culture surface is significantly lowerafter reprogramming. Only at around day 5 after transfection(s) thecells that received sufficient load of reprogramming material willadhere and start to form colonies of fully or partially reprogrammedcells. Similar to the above-mentioned methods with adherent cells, thecell culture system is trained to distinguish the most promisingsingle-cell derived colonies at an early stage and keep them isolated byremoving any unwanted cells surrounding the emerging colonies andeventually all other cells in the growth area.

In addition, the cell culture system disclosed herein does not requiresingle-cell plating, limiting dilution or repeated colony picking tocreate clonal populations of cells. The process of deriving clonalhiPSC-populations from single cells has been shown to be highlyineffective due to increased cell death upon 48 h after plating. Thebiological mechanism behind this phenomenon is poorly understood. Toincrease cloning efficiency, low-density plating is commonly used toensure cell survival, but often at the cost of clonality. Despite thebetter survival, this method requires frequent imaging to ensure thatthe cells do not migrate and form a polyclonal colony. Once detected,these wells with polyclonal colonies need to be excluded from theexperiment, leading to loss of money. Indeed, it has been shown thatwhen plated closer than 150 μm apart hiPSCs tend to move together toform a colony. To date, there are no technologies able to control thedistance of the cells when plated in low density fashion.

However, the cell culture system may be configured to fully reprogramhiPSCs plated at the density most likely to yield in cell separation ofat least 150 μm. Due to the random plating location of each cell, thecell editing subsystem may be configured to remove any cell that residescloser than 150 μm from its neighbor, reducing the chances of polyclonalcolony formation. To improve the number of monoclonal lines, low-densityplating is followed by repeated rounds of hiPSC colony picking, which isnot necessary when using the cell culture system. These directlytranslate into reduced manufacturing costs per clonal hiPSC-line whencompared to methods based on single-cell plating or low-density platingfollowed by repeated clonal picking. An additional advantage of thisapproach is that the total number of cell divisions is kept to a minimumwhen compared to post-reprogramming clonality enforcement. It is knownthat hiPSCs are particularly prone to genetic or karyotypicalvariations, and that the load of these variations grows with the numberof cell divisions (or related, “passages”). By enforcing clonality fromthe start of reprogramming, the full resulting population of hiPSCs atthe end of the reprogramming process may be used for quality control andfor the application at hand, rather than as the input to a process thatrestarts from a single cell.

FIGS. 21A-C are diagrams illustrating a portion of a process for iPSCreprogramming in accordance with various implementations. Specifically,FIGS. 21A-C depict the cell seeding and early reprogramming phases inwhich somatic cells are seeded into a cell culture container, havingeither had reprogramming factors delivered prior to seeding, or factorsdelivered in the chamber itself. FIG. 21A shows an example cell culturechamber 2102, shown here as a fluidic chamber with two ports forfilling/removal, and media circulation. The cell culture chamber 2102 isinoculated (shown by arrow 2104) and non-reprogrammed input cells 2106then settle in the cell culture chamber 2102. For example, thereprogramming process may utilize CD34+ cells that have had episomalvectors delivered prior to inoculation via electroporation. FIG. 21Bshows the emergence of pre-IPS cells 2108 from a subset of thenon-reprogrammed input cells 2106 after some period of time. Generally,cells that have some degree of reprogramming will become adherent to asurface that has a supporting matrix. FIG. 21C shows an initial mediaexchange in the cell culture chamber 2102, where fresh media 2110displaces the initial media, and in the process cells that have notbecome adherent (which exclude the pre-IPS cells 2108) are washed out asindicated by arrow 2116.

FIGS. 22A-B are diagrams illustrating cell removal during an iPSCreprogramming process in accordance with various implementations. Cellremoval may be conducted to limit initial cell attachment and growth toan area where it is not perturbed by cell culture container edges oredge liquid/thermal/chemical gradient effects. FIG. 22A shows a designedarea 2202 in a cell culture chamber that is designated for initial cellemergence. The designed area 2202 may be designed such that coloniesthat emerge within the designed area 2202 have room to grow beforehitting the designated boundary away from the cell culture chamber edge(indicated by the outer dashed line). Cells that are outside of thisinitial boundary, denoted as cells 5304, are identified and removedusing a cell removal mechanism (e.g., cell editing subsystem 114 in FIG.1 ). This cell removal mechanism may be optical (laser), acoustic(focused ultrasound), mechanical, etc. but should be able to lyse,destroy, and/or lift cells off the growth surface. In any case thisremoval mechanism should be steered by a computing system (e.g.,computing subsystem 110 in FIG. 1 ). Preferably, the cell removalmechanism performs this action without any need to open the cell culturecontainer (i.e., it is compatible with closed containers/media systems).The cell removal mechanism may either target individual cells asidentified through imaging, or sweep the entire area outside of thedesignated boundary. FIG. 22B shows the resulting cell population afterremoval of out-of-bounds cells, and appropriate washing to remove celldebris.

FIGS. 23A-C are diagrams illustrating cell isolation during an iPSCreprogramming process in accordance with various implementations. A cellremoval mechanism (e.g., cell editing subsystem 114) may be used toisolate single cells in clusters of emerging iPSC candidates. FIG. 23Ashows a cell culture chamber that includes a mix of source somatic(un-reprogrammed) cells and emerging iPS cells in small colonies 2302.Each of these colonies 2302 often corresponds to a single source cell.For example, in a case where CD34+ cells are being reprogrammed usingepisomal vectors delivered via electroporation, reprogramming efficiencyis approximately 0.05% per cell. Thus in a container with 10,000 CD34+cells it would be expected that, on average, 5 cells will emerge asiPSCs. Statistically these cells are unlikely to emerge immediatelyadjacent to one another, but in some cases they may be close enough toeach other that they may merge into a single colony and losemonoclonality.

The cell culture system disclosed herein may ensure monoclonality usinga combination of imaging, image processing from label-free images todetermine precise cell location coordinates, a method for computing anoptimal set of cell removals, and a mechanism for individually removingor terminally damaging the selected cells. This results in a singleviable cell isolated within a sufficiently large area such that therewill be no “cross-contamination” between already-emerging iPS clones,nor with yet-to-emerge iPS cells from proximate somatic cells. Thisselection and deletion process is shown in FIG. 23B. Selected iPScandidate cells 2304 are identified and have virtual perimeters 2306drawn around them. Any cells lying within these perimeters that are notthe selected iPS candidates are marked for removal/destruction, and thecell removal mechanism lyses/irreparably damages/removes them from theculture as indicated by outlined cell colonies 2308. After removal, theselected emerging iPS cells are left as single cells within theperimeters as illustrated in FIG. 23C with “clonal perimeters” 2310.

FIGS. 24A-C are images illustrating cell isolation during an iPSCreprogramming process in accordance with various implementations. FIGS.24A-C show real images taken from a cell culture chamber undergoing theprocess described with respect to FIGS. 23A-C. The cells in FIGS. 24A-Care iPS cells emerging from CD34+ cells during reprogramming. In FIG.24A a number of CD34+ cells 2404 (approximate cell diameter 10 microns,for reference) showing no signs of reprogramming are located in theneighborhood of a cluster of cells that show signs of successfulreprogramming including a “selected” cell 2402 and several connected“unselected” cells 2406. As described above, the goal is to isolate theselected cell as the only viable cell in the local region. FIG. 24Bshows a pattern of points 2408 that were targeted by a cell removalmechanism (e.g., cell editing subsystem 114), which in this case is ananosecond pulsed laser (<10 ns pulse width, 532 nm) that is focused ona 20 nm Titanium semi-absorbing film on the cell growth surface. Theresulting explosive microbubbles lyse and detach the target cells, whileinducing little collateral damage in surrounding cells, specifically theselected iPS candidate cell 2402. In FIG. 24C a cell viability stain isused to demonstrate the viability of the selected cell 2402, and also todemonstrate that no other viable cells remain within the field of view.

FIGS. 25A-C are diagrams illustrating non-iPS cell removal during aniPSC reprogramming process in accordance with various implementations.For example, certain cells may start differentiating into non-iPS celltypes during cell culture and thus should be removed. In some cases,there may be failed partial reprogramming that causes the source somaticcells to differentiate into non-iPS cells 2502, which may potentiallycontaminate the emerging iPSC candidate cells or colonies 2506. Thesecells are located and classified by a computing subsystem as non-sourceand non-iPS candidates by their distinct morphological characteristicsusing image analysis. The non-iPS cells may be distinguished from as-yetun-reprogrammed source cells 2504 or emerging iPSC candidate cells orcolonies 2506, which should remain. To prevent non-iPS cells fromproliferating and contaminating the iPS cell culture, these errant cellsare identified and then removed using a cell removal mechanism (e.g.,cell editing subsystem 114), as shown in FIG. 25B. The non-iPS cells maybe identified, located, and targeted by the cell removal mechanism.Subsequently, the cell culture chamber contains only source somaticcells and iPS candidate cells as shown in FIG. 25C.

FIGS. 26A-B are diagrams illustrating neighboring cell removal aroundiPSC colonies during an iPSC reprogramming process in accordance withvarious implementations. This may be done to ensure continued clonalityof the iPSC colonies. FIG. 26A shows an example where there are threeclonal iPS-like colonies with corresponding exclusion zones 2602designed to maintain clonality by removing any cells not clearlybelonging to the original clonal colony. The size of these zones may bedetermined by the interval between imaging/selective cell removal, theexpected area growth rates of the colonies, and the expected rate ofemergence of other iPS candidates from somatic cells. Any neighboringcells 2604 not clearly belonging to the clonal colonies that aredetected inside these clonal zones may be considered contaminant cells,are marked for deletion, and deleted. After deletion (which may includedirect removal, or destruction and subsequent removal through washing),the exclusion zones 2602 are again demonstrably clonal in origin. In allthe selective removal operations depicted in the current disclosure,re-imaging after removal and washing may be used to confirm removal oftarget cells. Any cells that remain may be retargeted with a cellremoval mechanism (e.g., cell editing subsystem 114) until removal iscomplete.

FIGS. 27A-B are diagrams illustrating removal of cells that break offfrom iPSC colonies during an iPSC reprogramming process in accordancewith various implementations. Cells that break off from clonal iPSCcandidate colonies and move beyond a defined perimeter around thosecolonies may endanger clonality of the verified-clonal colonies. Thisoperation is analogous to the process described with respect to FIGS.26A-B, except applied to cells whose origin cannot be traced to theclone owning the exclusion zones 2702. These potentially-escaped cells2704 are considered contaminant cells and should be removed because ifthey cannot be traced back to an originating colony, it may be a cloneof the colony. If the iPS-like cells can be traced to the local clone,then the exclusion zone 2702 may be widened to contain the cellsinstead. Note the circular zones drawn in FIGS. 27A-B are here are onlyfor illustration. In most cases the exclusion zones will be adistanced-based metric from the nearest known cells belonging to thespecific clone, to define a polygonal exclusion zone. After a cellremoval mechanism (e.g., cell editing subsystem 114) removes thepotentially-escaped cells 2704, the pure clonal zones are shown in FIG.27B with no extraneous cells in their exclusive zones 2702.

FIGS. 28A-B are diagrams illustrating removal of non-iPS cell candidatesduring an iPSC reprogramming process in accordance with variousimplementations. At a timepoint at which new iPS colonies are unlikelyto emerge from somatic cells, the remaining somatic cells (for exampleCD34+ cells that have had episomal vector delivered) are consideredcontaminant cells and are actively removed from the cell culturechamber, as shown in FIG. 28A in which non-reprogrammed cells 2804 aretargeted and removed while leaving iPSC colonies 2802 alone. Afterclearing of remaining un-reprogrammed cells, only iPS colonies 2802remain as shown in FIG. 28B.

FIGS. 29A-C are diagrams illustrating removal of a cell colony during aniPSC reprogramming process in accordance with various implementations.Cell colonies may be removed when, for example, two clonal colonies ofdifferent clonal origin are in danger of colliding andcross-contaminating. The cell culture system disclosed herein has theadvantage that through continuous imaging, tracking, and isolation ofclonal colonies, it can allow multiple clonal colonies to co-exist in acell culture container without the possibility of cross-contamination ofclones (i.e. creation of non-clonal colonies). As a result, the behaviorof each colony is more uniform due to its clonal origin, and ultimatelyno post-reprogramming clone process is required to ensure valid qualitycontrol results. Clone behavior can be tracked over time, and when aclone is determined to be poor, or when two clones are in danger ofcolliding in the container, one clone may be selected for removal.

FIG. 29A shows two clonal colonies 2904 and 2906 that have beendetermined to be in danger of colliding within the next imaging/editingperiod, as indicated by the border 2902. In this example, the clone 2906has been determined to have a higher probability of yielding a good iPSCclone. These determinations may be made by a computing subsystem (e.g.,computing subsystem 110) in coordination with a cell imaging subsystem(e.g., imaging subsystem 112), or may be determined by manualobservation and selection, or a combination of automation and manualobservation/selection. As a result, as shown in FIG. 29B, the collidingbut (by prediction) inferior clone 2904 is selected for removal. Afterremoval, as shown in FIG. 29C, the selected clone 2906 is now in nodanger of collision or cross-clone contamination.

FIGS. 30A-B are images illustrating removal of a cell colony during aniPSC reprogramming process in accordance with various implementations.In the example shown in FIGS. 30A-B, a terminal decision may be made inwhich a single clone/colony is selected to make a single clonal samplein the cell culture container. In FIG. 30A, a desired colony 3002 isselected by manual or automatic means (e.g., by a computing subsystem).A number of other (nonselected) colonies 3004 are present in the cellculture container. In this example, the images shown are brightfieldmicroscopy images of a single well on a 96-well microplate. The brighter(colony) regions are in fact an array of points plotted over the imagethat represent the extract (x, y) coordinates of each cell, as predictedby a deep learning algorithm that effectively converts brightfieldimages into cell nuclear coordinates. A polygon image of the desiredcolony 3002 represents a selection of those cells that is selected toremain in the container. The inverse of this cell selection is used toguide removal). FIG. 30B shows an image acquired 24 hours after cellremoval by pulsed laser, in which the selected colony 3002 is the soleremaining colony (and has proliferated). The other colonies have beenremoved so that the microplate well is open for the selected colony 3002alone to proliferate and expand.

FIGS. 31A-C are diagrams illustrating selection of a cell colony duringan iPSC reprogramming process in accordance with variousimplementations. This illustrates the ultimate selection of a singleclonal colony to create the output iPS cell product. A cell removalmechanism (e.g., cell editing subsystem 114) is used to remove any othercells or colonies not stemming from the selected clone. In FIG. 31A, aselected colony 3102 is retained while any other colonies 3104 aremarked for removal and removed by the cell removal mechanism as shown inFIG. 31B. Ultimately only the selected colony 3102 remains in thecontainer, as shown in FIG. 31C. The non-presence of any other cells inthe well may be checked by one or more subsequent imaging runs, and anyremaining cells removed using the cell removal mechanism (andappropriate washing) until it is verified that only the desired clonalcolony 3102 is present.

FIGS. 32A-C are diagrams illustrating spreading of a cell colony in acell culture chamber during an iPSC reprogramming process in accordancewith various implementations. Specifically, a cell removal mechanism(e.g., cell editing subsystem 114) may be used to break apart one ormore cell colonies derived from a common cell (i.e., a monoclonalcolony), followed by detachment of the fragments of the colony/colonies,and distribution over the cell culture container so as to providemaximum space for expansion of the clone. In the example shown in FIGS.32A-C, a clonal colony is sectioned into pieces, then gently lifted offthe cell culture surface, and then distributed across the cell culturechamber in order to seed a uniform expansion of the clone. In FIG. 32A,a clonal colony 3202 is treated with a selective cell removal mechanismacting on a subset of cells 3204, which are then removed from the cellculture container. After removal of the subset of cells 3204 as shown inFIG. 32B, the clonal colony 3202 has been fragmented. The individualcolony fragments are easier to lift off the cell growth surface usingtrypsinization or any similar process. The pieces, once in suspension,may then be redistributed around the container as shown in FIG. 32C.FIGS. 32D-32E show an initial colony controlled for density that spreadover a growth chamber. As shown in FIG. 32D, a single colony is dividedinto four pieces with laser processing. Next, as shown in FIG. 32E, thedivided pieces of the colony continue to grow, with some preference tooutward direction, after washing and continued cell culture.

FIGS. 33A-B are diagrams illustrating removal of cells outside ofdesignated regions during an iPSC reprogramming process in accordancewith various implementations. Cells growing outside of designatedregions of the cell culture chamber may be removed to prevent cellgrowth in border regions of the cell culture container where mediaconditions, chemical gradients, temperature, flow rate/shear, convectionmay be less uniform or consistent. FIG. 33A depicts a number of cells3304 that are outside of a designated region 3302 of the cell culturechamber. The cells 3304 may be identified and removed using a cellremoval mechanism (e.g., cell editing subsystem 114), such thatafterwards all cells in the cell culture chamber are growing within thedesignated region 3302.

FIGS. 34A-C are images illustrating removal of various cells during aniPSC reprogramming process in accordance with various implementations.Cells may be removed during the cell culture process for a number ofreasons, including cells that (a) proliferate outside the designatedgrowth area, (b) grow to excessive density within colonies, or (c)spontaneously differentiate. FIG. 34A depicts a cell culture chambercontaining a variety of cells, including iPSCs 3402 that are atdesirable density and without spontaneously differentiating cells,spontaneously differentiated cells 3404, regions of iPSC colonies 3406that are too high a density due to internal colony proliferation, andcells 3408 pushing over the established boundary for cell growth. It isdesirable to control the internal density of iPSC colonies such that allcells remain observable in label-free imaging, all cells remainremovable by a cell removal mechanism (e.g., cell editing subsystem114), and cells do not grow to a density at which they spontaneouslydifferentiate or form 3D structures that tend to differentiate. Asdepicted in FIG. 34B, the spontaneously differentiated cells 3404, highdensity colonies 3406, and boundary cells 3408 are all designated ascontaminant cells targeted for removal 3410 via imaging (e.g., imagingsubsystem 112) and downstream computation (e.g., computing subsystem110). The cell culture system may determine the coordinates of thetargeted cells 3410 and then remove them using the cell removalmechanism. The resulting cell culture is free of these potentialimpairments to a high-quality clonal iPSC culture, as shown in FIG. 34C.

FIGS. 35A-C are diagrams illustrating fragmenting of a cell colony in acell culture chamber during an iPSC reprogramming process in accordancewith various implementations. Once a clonal cell colony reaches amaximum confluency (e.g., it grows to fill the entirety of thedesignated growth region of a cell culture chamber), a cell removalmechanism (e.g., cell editing subsystem 114) may repeatedly remove someof the cells to allow for multiple divisions of iPS cells(conventionally known as “passages,” but as implemented herein does notrequire removal of the clonal iPS cells from the cell growth surface orcell culture container). This may, for example, enable clearance of areprogramming vector including, but not limited to, episomal vectors,Sendai virus, or self-replicating mRNA. In this example, the cell countis reduced and growth areas are opened using the cell removal mechanism,but cells are removed in a biologically-relevant manner that leaves iPScells in contact with clusters neighboring cells.

A clonal iPSC cell culture 3502 approaching high or full confluency isdepicted in FIG. 35A. FIG. 35B shows a method of reducing cell count toallow cell division without overcrowding, and therefore vector clearing.Namely, a cell removal pattern 3504 is calculated based on cell imagingthat leaves iPSC structures with sufficient iPSC numbers and neighborcontacts that maintain iPSC health. This is akin to clumped passaging ofiPS cells in conventional container-to-container passaging, but allowsthe process to be conducted in a single container, which significantlysimplifies the process, reduces consumable usage, lowers stress on theremaining cells, and allows the process to be performed inside of aclosed, sterile container, isolated from other patient samples andpotential contaminants. A computing subsystem (e.g., computing subsystem110) may determine the cell removal pattern 3504 from images obtainedfrom a cell imaging subsystem (e.g., imaging subsystem 112). FIG. 35Cshows the remaining cell colony 3506 after the cell removal mechanismhas removed the cell removal pattern 3504. The cell colony 3506 may nowundergo further cell division into the resulting gaps, while keepingsufficient connection between cells to maintain cell health and chemicaland mechanical signaling, which is often lost during conventionalpassaging. It should be noted that a number of patterns that meet thesecriteria are possible, for example an “island positive” pattern such asthe one shown here (where on average convex islands of cell remain,surrounded by a network of cleared areas), or “island negative” wherecells form a network around cleared convex areas.

FIGS. 36A-B are images illustrating fragmenting of a cell colony in acell culture chamber during an iPSC reprogramming process in accordancewith various implementations. FIGS. 36A-B are images illustrating theoperation described with reference to FIGS. 35A-C on actual cells. FIG.36A shows a cell culture container (e.g., a single well within a 96-wellplate) with iPS cells that have been Calcein AM (live cell stain)labelled. Near the top of the well, the iPS cells have reached highdensity in region 3602. The cells were imaged in label-free brightfield(not shown) imaging, and a deep learning network was used to extract (x,y) coordinate positions of all cells. The cell positions were used tocalculate local density. Where density was higher than desirable as inthe region 3602, a pattern of cell removals that left intact contiguousnetworks of iPSCs was calculated. As can be observed from the differencebetween images in FIG. 36A (prior to selection and removal) and FIG. 36B(after selective removal of cells), the region 3602 has had densitydecreased significantly, while leaving a viable network of iPSCs (asindicated by the Calcein AM cell viability stain) for furtherproliferation. This process may be repeated to clear reprogrammingvectors from the iPSCs. Another example of cell removal and subsequentregrowth is illustrated in FIGS. 36C-D. FIG. 36C shows a dense hiPSCcell culture removed using laser microbubble lysing and washing. FIG.36D shows regrowth of the hiPSC cell culture after 24 hours.

FIGS. 37A-C are diagrams illustrating harvesting of cells in a cellculture chamber during an iPSC reprogramming process in accordance withvarious implementations. In this example, a cell removal mechanism(e.g., cell editing subsystem 114) is used to prime the cell culture byopening up gaps between small islands of cells, making the subsequentremoval with an agent such as Trypsin gentler (e.g., requiring lessexposure time), before removal of the clonal iPS cells in suspension.FIG. 37A depicts a clonal cell colony 3702 produced with the systems andmethods disclosed herein, approaching full confluency. The cellpopulation may be directly treated with trypsin for liftoff and harvest.However, in this example, a selective cell removal mechanism may be usedas shown in FIG. 37B to selectively remove a sparse set of cells 3704that cuts the clonal cell colony 3702 into smaller islands prior tolift-off into suspension. Finally, as shown in FIG. 37C, clonal cells3706 from the clonal cell colony 3702 may be harvested in suspensionfrom the cell culture container.

The operations described with respect to FIGS. 21A-37C may be conductedby a cell culture system as disclosed herein (e.g., cell culture system100). The cell culture system may provide a closed system for cellculture growth (e.g., a closed cassette system), as well as provideautomated imaging, cell editing, cell harvesting, cell monitoring andprediction, and other cell culture functions. In some implementations,the cell culture system may operate in a fully automated fashion withuser oversight of cell culture processes through user interfaces. Insome implementations, the cell culture system may also operate in asemi-automated fashion, in which users may manually conduct one or moreof the cell culture steps. For example, a user may manually observe thecell culture and identify cells and cell colonies that should be kept orremoved, and the cell culture system may use automated cell editingfunctions to remove the unwanted cells and cell colonies. Thus, the cellculture system disclosed herein may be configured to produce monoclonalcell output products, such as monoclonal iPSCs, in a closed system usingthe operations described with respect to FIGS. 21A-37C. The use ofautomated cell imaging and editing may help keep cell cultures clonalduring cell growth and proliferation. Because the output cell productsare to be used in various cell therapies and other medical applications,ensuring monoclonality is important for a variety of reasons such aspatient safety, differentiation/treatment efficacy, and adhering toapplicable statutes, regulations, and standards concerning celltherapies utilizing the output cell products.

Remote Actuator Systems

Closed or sealed cell culture systems are important for producingclinical-grade cells or biologics at scale. Closed systems arepreferable to open systems, in which contamination orcross-contamination are an ever-present danger and expensive, high-gradecleanrooms and regular sterilization regimes are required. Mostsmall-scale adherent cell culturing is done in 2D vessels such as wellplates or flasks. An advantage of these containers is that the cellcultures may be inspected by microscopy. However, such containers areopen systems. For example, they are opened for regular cell mediachanges or operations on the cell culture itself, for example passagingor colony selection.

Stirred bioreactors offer a closed cell culture environment and may beused for adherent cells with appropriate use of cell aggregates ormicrocarriers that provide a niche for adherent cell growth. Inaddition, they provide good continuous mixing of cell media, meaningnutrients and dissolved gases are efficiently mixed and transported tocells, and waste products carried away. However, there is no ability toobserve cell behavior via imaging, much less editing the cell culture inthese systems.

Formats for 2D adherent cell cultures scale up in a semi-closed orclosed environment, enable large area 2D adherent growth, and to alimited extent can enable observability by microscopy. However, theyoften provide uneven distribution of nutrients and dissolved gases, andthe only solution is to flow media faster through the cell culturechamber, which can lead to systematic stress on cell cultures and changein gene expression, health, and/or phenotype. Thus what is needed in theart are methods of enabling 2D adherent cell culture in a closed cellculture chamber. The closed cell culture chamber should enable a numberof functions, such as observation by microscopy, cell editing, andliquid handling (such as media mixing, cell layer washing, debrisremoval), all without breaking the seal on the closed cell culturechamber or the liquid loop within it.

The systems and methods disclosed herein enable a cell culture system tomonitor and dynamically manipulate the contents of a closed cell culturechamber of a cell culture container (e.g., cell culture container 106 inFIG. 1 ). These system and methods include one or more magnetic toolsthat function inside of a closed cell culture chamber in which adherentcells are cultured in two dimensions. The magnetic tools may reside onthe surface opposite of the adherent cell culture and are magneticallycoupled to external actuators that control rotation, translation, andorientation of the magnetic tools in order to provide a variety offunctions, including but not limited to: mixing of media to ensureuniform distribution of nutrients, dissolved gasses, cell factors, otherreagents, waste products, etc.; agitation to dislodge and wash debrisaway from the cell culture surface; detaching non-adherent cells from anadherent cell culture; moving debris to a collection region; ensuringuniform distribution of cells during seeding; and dislodging and washingaway cells during cell harvesting.

FIGS. 38A-B are block diagrams of a closed cell culture container with amagnetic tool in accordance with various implementations. FIG. 38A showsa cross-section view of a cell culture container 3800 a with an engagedmagnetic tool. The cell culture container 3800 a may be similar to cellculture container 106 in FIG. 1 , and may be part of a cell culturesystem. A liquid-filled cell culture chamber 3802 is enclosed by acell-bearing surface 3804 and an opposite surface 3806. These surfacesare typically glass or polymer sheets. In many cases both aretransparent to facilitate imaging of the cell culture 3808 on thecell-bearing surface 3804. In this example, an inverted cell culture isshown, where after inoculation of the cell culture chamber 3802, thevertical orientation of the chamber is opposite of what is shown in FIG.38A, causing cells to settle and then adhere to the cell-bearing surface3804 due to the forces of gravity. After the cells adhere, the cellculture chamber 3802 is inverted or turned around, and the majority ofthe cell culture process is performed in an inverted orientation suchthat debris or non-adherent cells settle on the opposite surface 3806,where they may be removed using the systems and methods disclosedherein.

An internal magnetic tool 3810 resides inside of the closed cell culturechamber 3802, opposite of an external magnetic component 3812. Theinternal magnetic tool 3810 may be pushed against the inside of theopposite surface 3806 because of magnetic attraction to the externalmagnetic component 3812. The internal magnetic tool 3810 may include oneor more magnets that are coated appropriately for a biologicalenvironment. For example, a rectangular Neodymium rare Earth magnet maybe coated with a polymer or fluoropolymer to make it inert,biocompatible, non-stick, and non-scratching as it translates or rotateson the inner surface of the cell culture chamber 3802. The externalmagnetic component 3812 may also be coated to prevent scratching of theouter surface of the cell culture chamber 3802.

The external magnetic component 3812 may be removably coupled to anactuator 3814 that may be configured to rotate the external magneticcomponent 3812, and by extension the internal magnetic tool 3810, aroundrotation axis 3816. The actuator 3814 may in turn be translated aroundthe same plane as the opposite surface 3806 to allow the internalmagnetic tool 3810 to traverse the entire surface of the cell culturechamber 3802. This, along with the rotation action of the actuator 3814,gives the internal magnetic tool 3810 three degrees of freedom (i.e.,motion in the XY plane of the opposite surface 3806, and motion aroundthe rotation axis 3816). The translation mechanism for the actuator 3814is not shown in FIG. 38A. In one example, the actuator 3814 may beconnected to one or more arms that move the actuator 3814 around the XYplane and may move the actuator 3814 towards or away from the oppositesurface 3806. The one or more arms may be controlled by a computingsubsystem in a cell culture system (e.g., system 110 in FIG. 1 ). Ingeneral, the actuator 3814 may be translated relative to a stationarycell culture chamber 3802, or vice versa.

FIG. 38B shows a cross-section view of a cell culture container 3800 bhaving the same components as cell culture container 3800 a, except thatthe external magnetic component 3812, and by extension the internalmagnetic tool 3810, are disengaged from the actuator 3814. In FIG. 38B,the actuator 3814 has been retracted from the cell culture chamber 3802.The actuator 3814 may have one or more mechanisms that allow theactuator 3814 to capture or connect to the external magnetic component3812 and disconnect from it. The internal magnetic tool 3810 and theexternal magnet component 3812 remain in place but are stationary due tothe magnetic forces between them, and the resulting friction forcesagainst the surface 3806, preventing the internal magnetic tool 3810from freely moving around the cell culture chamber 3802. Thus the cellculture container 3800 b may be moved locations while the internal andexternal magnetic components 3810, 3812 stay fixed in place so that theydo not damage the cell culture 3808. In some implementations, multipleinternal magnetic tools 3810 and associated external magnetic components3812 may reside on internal side and external sides, respectively, ofthe lower surface 3806. The actuator 3814 may engage with differentexternal magnetic components 3812 in order to move each internalmagnetic tool 3810 as needed to perform operations inside of the cellculture chamber 3802.

FIG. 38C shows dye in a liquid chamber of an exemplary micro-magnetictool. FIG. 38D shows an exemplary micro-magnetic tool being translatedthrough liquid from right to left by an actuator external to liquidchamber. As shown, the exemplary micro-magnetic tool is oriented tomatch direction of travel for minimum disturbance of the liquid. FIG.38E shows an exemplary micro-magnetic tool being translated throughliquid from right to left and counter-clockwise by an actuator externalto liquid chamber. As shown, the fluid is locally mixed in the treatedarea.

The exemplary tool shown in FIGS. 38A-C comprises rare earth magnets(dimensions: 5.0 mm×0.5 mm×0.5 mm) inside a liquid chamber. Externally(under the cell culture container wall and a sheet of white paper, forphotographic clarity), a motorized actuator with one axis of translationand one axis of rotation is placed under the magnetic tool and orientsthe tool in the cell culture vessel. In one example the cell culturevessel has a growth area of about 636 cm² and a chamber height of about17 mm.

In some implementations, the cell culture vessel has a growth area ofabout 400 cm² to about 5000 cm². In some implementations, the cellculture vessel has a growth area of at least about 400 cm², about 450cm², about 500 cm², about 550 cm², about 600 cm², about 650 cm², about700 cm², about 750 cm², about 800 cm², about 850 cm², about 900 cm²,about 950 cm², about 1000 cm², about 1100 cm², about 1200 cm², about1300 cm², about 1400 cm², about 1500 cm², about 1600 cm², about 1700cm², about 1800 cm², about 1900 cm², about 2000 cm², about 2500 cm²,about 3000 cm², about 3500 cm², about 4000 cm², about 4500 cm², or about5000 cm². In some implementations, the cell culture vessel has a growtharea of at most about 400 cm², about 450 cm², about 500 cm², about 550cm², about 600 cm², about 650 cm², about 700 cm², about 750 cm², about800 cm², about 850 cm², about 900 cm², about 950 cm², about 1000 cm²,about 1100 cm², about 1200 cm², about 1300 cm², about 1400 cm², about1500 cm², about 1600 cm², about 1700 cm², about 1800 cm², about 1900cm², about 2000 cm², about 2500 cm², about 3000 cm², about 3500 cm²,about 4000 cm², about 4500 cm², or about 5000 cm².

According to some implementations, the cell culture vessel is scaleddown to have a smaller growth area that is nonetheless sufficient forthe cell culture processes disclosed herein, thereby providing greaterefficiency in the use of space and resources (e.g., culture media,gases, power, rack space, etc.). In some implementations, the cellculture vessel has a growth area of about 5 cm² to about 500 cm². Insome implementations, the cell culture vessel has a growth area of about5 cm² to about 10 cm², about 5 cm² to about 50 cm², about 5 cm² to about100 cm², about 5 cm² to about 200 cm², about 5 cm² to about 300 cm²,about 5 cm² to about 400 cm², about 5 cm² to about 500 cm², about 10 cm²to about 50 cm², about 10 cm² to about 100 cm², about 10 cm² to about200 cm², about 10 cm² to about 300 cm², about 10 cm² to about 400 cm²,about 10 cm² to about 500 cm², about 50 cm² to about 100 cm², about 50cm² to about 200 cm², about 50 cm² to about 300 cm², about 50 cm² toabout 400 cm², about 50 cm² to about 500 cm², about 100 cm² to about 200cm², about 100 cm² to about 300 cm², about 100 cm² to about 400 cm²,about 100 cm² to about 500 cm², about 200 cm² to about 300 cm², about200 cm² to about 400 cm², about 200 cm² to about 500 cm², about 300 cm²to about 400 cm², about 300 cm² to about 500 cm², or about 400 cm² toabout 500 cm², including increments therein. In some implementations,the cell culture vessel has a growth area of about 5 cm², about 10 cm²,about 50 cm², about 100 cm², about 200 cm², about 300 cm², about 400cm², or about 500 cm². In some implementations, the cell culture vesselhas a growth area of at least about 5 cm², about 10 cm², about 50 cm²,about 100 cm², about 200 cm², about 300 cm², or about 400 cm². In someimplementations, the cell culture vessel has a growth area of at mostabout 10 cm², about 50 cm², about 100 cm², about 200 cm², about 300 cm²,about 400 cm², or about 500 cm².

In some implementations, the cell culture vessel has a chamber height ofabout 12 mm to about 50 mm. In some implementations, the cell culturevessel has a chamber height of at least about 12 mm, about 13 mm, about14 mm, about 15 mm, about 16 mm, about 17 mm, about 18 mm, about 19 mm,about 20 mm, about 30 mm, or about 40 mm. In some implementations, thecell culture vessel has a chamber height of at most about 13 mm, about14 mm, about 15 mm, about 16 mm, about 17 mm, about 18 mm, about 19 mm,about 20 mm, about 30 mm, about 40 mm, or about 50 mm.

In some implementations, the cell culture vessel has a chamber height ofabout 0.05 mm to about 10 mm. In some implementations, the cell culturevessel has a chamber height of about 0.05 mm to about 0.1 mm, about 0.05mm to about 0.5 mm, about 0.05 mm to about 1 mm, about 0.05 mm to about2 mm, about 0.05 mm to about 3 mm, about 0.05 mm to about 4 mm, about0.05 mm to about 5 mm, about 0.05 mm to about 6 mm, about 0.05 mm toabout 8 mm, about 0.05 mm to about 10 mm, about 0.1 mm to about 0.5 mm,about 0.1 mm to about 1 mm, about 0.1 mm to about 2 mm, about 0.1 mm toabout 3 mm, about 0.1 mm to about 4 mm, about 0.1 mm to about 5 mm,about 0.1 mm to about 6 mm, about 0.1 mm to about 8 mm, about 0.1 mm toabout 10 mm, about 0.5 mm to about 1 mm, about 0.5 mm to about 2 mm,about 0.5 mm to about 3 mm, about 0.5 mm to about 4 mm, about 0.5 mm toabout 5 mm, about 0.5 mm to about 6 mm, about 0.5 mm to about 8 mm,about 0.5 mm to about 10 mm, about 1 mm to about 2 mm, about 1 mm toabout 3 mm, about 1 mm to about 4 mm, about 1 mm to about 5 mm, about 1mm to about 6 mm, about 1 mm to about 8 mm, about 1 mm to about 10 mm,about 2 mm to about 3 mm, about 2 mm to about 4 mm, about 2 mm to about5 mm, about 2 mm to about 6 mm, about 2 mm to about 8 mm, about 2 mm toabout 10 mm, about 3 mm to about 4 mm, about 3 mm to about 5 mm, about 3mm to about 6 mm, about 3 mm to about 8 mm, about 3 mm to about 10 mm,about 4 mm to about 5 mm, about 4 mm to about 6 mm, about 4 mm to about8 mm, about 4 mm to about 10 mm, about 5 mm to about 6 mm, about 5 mm toabout 8 mm, about 5 mm to about 10 mm, about 6 mm to about 8 mm, about 6mm to about 10 mm, or about 8 mm to about 10 mm, including incrementstherein. In some implementations, the cell culture vessel has a chamberheight of about 0.05 mm, about 0.1 mm, about 0.5 mm, about 1 mm, about 2mm, about 3 mm, about 4 mm, about 5 mm, about 6 mm, about 8 mm, or about10 mm. In some implementations, the cell culture vessel has a chamberheight of at least about 0.05 mm, about 0.1 mm, about 0.5 mm, about 1mm, about 2 mm, about 3 mm, about 4 mm, about 5 mm, about 6 mm, or about8 mm. In some implementations, the cell culture vessel has a chamberheight of at most about 0.1 mm, about 0.5 mm, about 1 mm, about 2 mm,about 3 mm, about 4 mm, about 5 mm, about 6 mm, about 8 mm, or about 10mm.

In some implementations, the cell culture vessel has a scaled-downgrowth area and/or chamber height that is sufficient for the cellculture processes disclosed herein.

FIG. 39 is a three-dimensional view of a closed cell culture container3900 with a magnetic tool in accordance with various implementations.The cell culture container 3900 may be similar to cell culturecontainers 106, 3800, 3800 b in FIGS. 1, 38A, and 38B respectively. Aliquid-filled cell culture chamber 3902 includes two surfaces, an uppersurface 3904 and a lower surface 3906. Both surfaces 3904, 3906 may betransparent for imaging purposes. There is an internal magnetic tool3908 inside the cell culture chamber 3902, held onto the lower surface3906 by an external magnetic component 3910. In some implementations,the cell culture container 3900 may have more than one internal magnetictool 3910 and corresponding external magnetic component 3912, as shownin FIG. 39 . An actuator 3912 may move relative along the XY plane ofthe lower surface 3906, and may also move perpendicular to the XY plane(e.g., Z axis) in order to engage and disengage with external magneticcomponent(s) 3910. A rotation actuator 3914 may be used to rotate acapture mechanism 3916 to the correct angle to capture the externalmagnetic component 3910 when the actuator 3912 is raised. Aftercapturing the external magnetic component 3910, the actuator 3912 may bemoved around the XY plane to reposition the internal magnetic tool 3908.The rotation actuator 3914 may be used to rotate the internal magnetictool 3908 via the external magnetic component 3910. Rotation andtranslation of the external magnetic component 3910, and by extensionthe internal magnetic tool 3908, may occur simultaneously.

An imaging objective 3918 may be positioned on the opposite side of thecell culture chamber 3902 as the actuator 3912 (e.g., above the uppersurface 3904). The imaging objective 3918 may be part of an imagingsubsystem (e.g., imaging subsystem 112) of a cell culture system. Theimaging objective 3918 may also be translated relative to the XY planeof the cell culture chamber 3902. In some implementations, the imagingobjective 3918 and the actuator 3912 are fixed relative to one anotherin the XY plane but may have independent Z translators. In otherimplementations, they may be completely independent in the X, Y, and Zplanes. In yet other implementations, the imaging objective 3918 and theactuator 3912 may have one axis of common motion (e.g., the X axis),while they may move independently in the other two axes (e.g., the Y andZ axes).

The imaging objective 3918 may be configured to image the cell culture,for example a cell culture adherent to the inside of the upper surface3904. The imaging objective 3918 may be further configured determinelocation and rotation information of the internal magnetic tool(s) 3910within the cell culture chamber 3902. The location information may beused by a computing subsystem (e.g., computing subsystem 110 in FIG. 1 )to control the actuator 3912 to capture and move the internal magnetictool(s) 3910. The computing subsystem, along with an imaging subsystemthat locates the contents (e.g., cells, debris) of the cell culturechamber 3902 (e.g., imaging subsystem 112 in FIG. 1 ), may further guidethe actuator 3912 to perform tasks based on cell culture imaging orimaging of debris within the cell culture chamber 3902. In thisimplementation, an illuminating ring 3920 may be situated opposite theimaging objective 3918. The illuminating ring 3920 may provide fixedillumination for the imaging objective 3918, or may have multipleaddressable elements (such as LEDs) to allow for selective lighting.

Examples of image-guided functions of the internal magnetic tool(s) 3910include, but are not limited to: (a) imaging cells that have been placedinto the cell culture chamber 3902 prior to adherence, and using theinternal magnetic tool(s) 3910 to ensure uniformity of cell distributionprior to adhesion of the cells to the growth surface (e.g., the uppersurface 3904); (b) imaging cells placed into the cell culture chamber3902 and removing/pushing cells away from regions deemed not suitablefor cell culture growth; (c) imaging the cell culture, identifyingregions with attached debris or non-adherent cells that have some weakattachment, and using the internal magnetic tool(s) 3910 to wash/agitatethem off the cell culture surface (e.g., the upper surface 3904); (d)imaging the surface opposite the cell culture (e.g., the lower surface3906), identifying any areas where cells are growing, and clearing cellsoff the lower surface with the internal magnetic tool(s) 3910; (e)locating regions of the cell culture that have been damaged or destroyedby a cell editing mechanism (e.g., cell editing subsystem 114 in FIG. 1) and agitating the local medium to remove the cell debris from the cellculture surface (e.g., the upper surface 3904); (f) during cell harvest,locating regions that have not detached from the cell culture surface(by trypsinization or similar techniques) and agitating the local mediumto hasten the detachment of cells from the cell culture surface (e.g.,the upper surface 3904); (g) during cell culture, locating regions ofhigher or lower cell density, or specific phenotypic or othercharacteristics, and guiding local media mixing in order to enhancenutrient, waste product, or cell-generated factor distributionaccordingly (for example, ensuring adequate supply of nutrients and/ordissolved gases to dense cell colonies within a generally sparse cellculture); (h) imaging cell debris that has fallen to the surfaceopposite the cell culture surface (e.g., the lower surface 3906), andguiding the internal magnetic tool(s) 3910 to remove this debris fromthe cell culture chamber 3902; and (i) imaging may be used todynamically orient the internal magnetic tool(s) 3910 as they aretranslated along features within the cell culture chamber 3902 (e.g.,boundaries, entry/exit channels, or support posts/fluidic features) inorder to ensure full coverage of the chamber by the tools.

FIG. 40A is a block diagram of various modes of use for an internalmagnetic tool in a closed cell culture container in accordance withvarious implementations. In rotation mode 4002A, rotation of themagnetic tool is used to agitate local media and/or apply forces onlocal cells or debris. In translation mode 4004A, the magnetic tool maybe translated over the surface at an angle relative to the direction ofmotion in order to push cells or debris. Rotation and translation modes4002A, 4004A may be combined in multiple ways, including dynamicallyorienting the magnetic tool to follow chamber features or outlines. Inmovement mode 4006A, the magnetic tool may also be translated in anorientation that causes the least disruption to the local fluidicenvironment, for example if the magnetic tool should be moved to anotherlocation without disturbing the inside of the cell culture chamber. Thespeed of the magnetic tool may be varied depending on the function. Forexample, during rotation mode 4002A, the magnetic tool may be spun at ahigh speed to generate the necessary force to act on cells or debris.During movement mode 4006A, the magnetic tool may travel at a slow speedto avoid disturbing the fluid medium and the cells.

FIG. 40B illustrates rotation of an internal magnetic tool 4002B in aclosed cell culture chamber in accordance with various implementations.As the internal magnetic tool 4002B is rotated in a cell culturechamber, it creates turbulent flows 4004B. The turbulent flows 4004B maybe used for a variety of functions, such as mixing the fluid media inthe cell culture chamber and other functions disclosed herein. Rotationmay also be combined with translation of the internal magnetic tool toenable coverage over different regions of the cell culture container.

FIGS. 41A-B illustrate use of an internal magnetic tool in a cellculture chamber for mixing media in accordance with variousimplementations. In 2D cell cultures, a common issue is that staticmedia causes local depletion of nutrients or oxygen where cells aredense and/or active. Likewise, waste products may build up in theseregions. The typical solution is to circulate media through the chamberand mix it in the process. However, the constant, directional shearstress imparted by this media circulation may disrupt cell culturebehavior. For example, such motion may trigger differentiation of stemcells into epithelial cells. Moreover, continuous media circulation hasother overhead in terms of equipment, environmental handling, etc.Therefore, the ability to mix media locally within the cell culturechamber while keeping the cell culture steady is highly desirable. Thiswould enable the desirable aspects of stirred bioreactors while keepingcells in a fully observable (by imaging) and editable (by lasers orother suitable approaches) format.

In FIG. 41A, media near high-density cell culture regions 4102 has beendepleted of nutrients and is high in waste products as well ascell-derived factors that are valuable for cell-to-cell signaling. Inless dense cell culture regions 4104, the media still contains a highconcentration of nutrients. An internal magnetic tool 4106 is translatedthrough the cell culture chamber, and either the translation alone, ortranslation and rotation, may be used to mix the liquid contents of thechamber. The translational and rotational speed of the internal magnetictool 4106 may be regulated to allow for fluid mixing without detachingadherent cells from the cell bearing surface.

FIG. 41B shows the cell culture chamber after processing by the internalmagnetic tool 4106. The internal magnetic tool 4106 has distributed thecontents of the liquid media 4108 in the chamber, resulting in a moreuniform distribution of the media. This mixing process may be guided byimaging from an imaging subsystem and computing of cell density andcolony locations by a computing subsystem, potentially with the aid of amedia and or fluidic model, to optimize the mixing function for aparticular cell culture configuration and state.

FIGS. 42A-42C illustrate use of an internal magnetic tool in a cellculture chamber for removing debris in accordance with variousimplementations. The removal of debris may include “washing” ofnon-adherent or weakly adherent cells, cell remains, and various debris(which may include but are not limited to cell debris, dead cells,matrix, biochemical agglomerates, particulates, etc.).

FIG. 42A shows an example of a cell culture in a cell culture chamber,the cell culture including weakly adherent cells 4202, particulatesattached to the cell layer 4204, and dead cells 4206 on the cellculture-bearing surface of the cell culture chamber. An internalmagnetic tool 4208 traverses the cell culture. Specifically, theinternal magnetic tool 4208 may traverse areas with cells growing,particularly areas with dead cells/debris/weakly adherent cells asidentified by an imaging subsystem. The internal magnetic tool 4208 mayadditionally rotate to cause local turbulence and transient shearstresses on the cell layer. This will preferentially detach weaklyadherent cells 4202 from the remainder of the cell culture. FIG. 42Bshows the same cell culture after the internal magnetic tool 4208 hastraversed. Detached debris 4210, which may include one or more of theweakly adherent cells 4202, particulates 4204, and dead cells 4206, havesettled on the opposite surface of the cell culture chamber. Thedetached debris 4210 may sink to the bottom surface (assuming thedirection of gravity is pointing downwards in FIG. 42B) because theirdensity is higher than the cell medium. FIG. 42C shows another functionof a magnetic tool 4212, which may be the same tool as internal magnetictool 4208 in FIGS. 42A-B, or another specialized tool. The magnetic tool4212 may be configured to push away the detached debris 4210 to an exitport in the cell culture chamber.

In some implementations, the same process as shown in FIGS. 42A-42C maybe performed on the cell product itself, during the cell harvestingphase. For example, Trypsin or another disassociation agent may be addedto the cell culture chamber for a period of time in order to loosencell-cell and cell-surface bonds. The magnetic tool(s) 4208, 4212 may beused to ensure complete intrusion of the agent into the cell layers andgaps between cells. The magnetic tool(s) 4208, 4212 may then be used toprovide shear forces to hasten and/or improve the loosening of the cellsfrom each another and from the surface. Finally, after the cells fall tothe opposite surface due to their higher density, the magnetic tool(s)4208, 4212 may be used to harvest of the now detached cells from thecell culture chamber.

FIGS. 43A-43D illustrate another implementation of using an internalmagnetic tool in a cell culture chamber for removing debris inaccordance with various implementations. FIG. 43A-43D illustrate atop-down perspective of a cell culture chamber having sidewall sections4302. The sidewalls 4302 may be tapered in order to create a funnel 4304at one end of the cell culture chamber. The funnel 4304 may lead towardan outflow channel or tube. An internal magnetic tool 4306 may belocated on a first surface of the cell culture chamber. The firstsurface may also include debris 4308 that has settled from the uppercell-bearing surface (not shown in FIGS. 43A-43D).

FIG. 43A illustrates the internal magnetic tool 4306 angled and ready tobe translated across the cell culture chamber to provide a “plowing”function, in which debris in the path of the internal magnetic tool 4306are pushed towards the outflow channel at the funnel 4304 as ittraverses parallel to the funnel opening. FIG. 43B shows the result ofthe plowing motion after one traversal of the cell culture chamber.Debris 4308 that was in the path of the internal magnetic tool 4306 arepushed along with the tool, creating a cleared space 4310. The debris4308 is pushed downwards, in the direction of the funnel 4304 that leadsto an outflow channel. FIG. 43C shows the results of further passes ofthe internal magnetic tool 4306 across the cell culture chamber. As canbe seen, all the debris 4308 in the cell culture chamber is pushedcloser to the funnel 4304 as the internal magnetic tool repeatedlysweeps the surface of the cell culture chamber.

FIG. 43D shows an example of a flushing process to remove the debris4308 from the cell culture chamber. Bulk media flow may be used to pushthe debris 4308 from the cell culture chamber into the outflow channel.The flow may be continuous during the process described with respect toFIGS. 43A-43D to create an overall fluid flow in the direction of thefunnel 4304. Additionally, the cell culture chamber may be tilted in thevertical direction such that the funnel 4304 and the outflow channel arevertically lower than the opposite side of the cell culture chamber.This tilt further encourages the debris 4308 to move towards the funnel4304 via gravity during the removal process.

Cell Editing Using Remote Actuator Systems

In the implementations described with respect to FIGS. 38A-43D, theinternal magnetic tool in the cell culture chamber was located on theopposite surface as the cell culture. However, in other implementations,the internal magnetic tool may also be located on the same surface asthe cell culture. In these implementations, the configuration andoperation of the internal magnetic tool may be different to implement avariety of functions, such as cell removal or harvesting.

FIG. 44 is a block diagram of a closed cell culture container 4400 witha magnetic tool in accordance with various implementations. The cellculture container 4400 may be similar to cell culture container 106 inFIG. 1 , and may be part of a cell culture system. A liquid-filled cellculture chamber 4402 is enclosed by a cell-bearing surface 4404 and anopposite surface 4406. These surfaces are typically glass or polymersheets. In many cases both are transparent to facilitate imaging of thecell culture 4408 on the cell-bearing surface 4404. In this example, aninverted cell culture is shown, where after inoculation of the cellculture chamber 4402, the vertical orientation of the chamber isopposite of what is shown in FIG. 44 , causing cells to settle and thenadhere to the cell-bearing surface 4404 due to the forces of gravity.After the cells adhere, the cell culture chamber 4402 is inverted orturned around, and the majority of the cell culture process is performedin an inverted orientation such that debris or non-adherent cells settleon the opposite surface 4406.

An internal magnetic tool 4410 resides inside of the closed cell culturechamber 4402, opposite of an external magnetic component 4412. Theinternal magnetic tool 4410 may be pushed against the inside of thecell-bearing surface 4404 because of magnetic attraction to the externalmagnetic component 4412. The internal magnetic tool 4410 may include oneor more magnets that are coated appropriately for a biologicalenvironment. For example, a rectangular Neodymium rare Earth magnet maybe coated with a polymer or fluoropolymer to make it inert,biocompatible, non-stick, and non-scratching as it translates or rotateson the inner surface of the cell culture chamber 4402. The externalmagnetic component 4412 may also be coated to prevent scratching of theouter surface of the cell culture chamber 4402.

The external magnetic component 4412 may be removably coupled to anactuator 4414 that may be configured to rotate the external magneticcomponent 4412, and by extension the internal magnetic tool 4410, arounda rotation axis. The actuator 4414 may in turn be translated around thesame plane as the cell-bearing surface 4404 to allow the internalmagnetic tool 4410 to traverse the entire surface of the cell culturechamber 4402. This, along with the rotation action of the actuator 4414,gives the internal magnetic tool 4410 three degrees of freedom (i.e.,motion in the XY plane of the cell-bearing surface 4404, and motionaround the rotation axis). The translation mechanism for the actuator4414 is not shown in FIG. 44 . In one example, the actuator 4414 may beconnected to one or more arms that move the actuator 4414 around the XYplane and may move the actuator 4414 towards or away from thecell-bearing surface 4404. The one or more arms may be controlled by acomputing subsystem in a cell culture system (e.g., system 110 in FIG. 1). In general, the actuator 4414 may be translated relative to astationary cell culture chamber 4402, or vice versa.

FIG. 45A shows various views of an internal magnetic tool 4500A for useon a cell-bearing surface in accordance with various implementations.FIG. 45A shows a top view (top left), a side view (bottom), and threecross-sectional views (top right) for the internal magnetic tool 4500A.Each cross-sectional view A′, B′, and C′ correspond to the marked A, B,C points of the top view. The internal magnetic tool 4500A may have anasymmetric shape. The internal magnetic tool 4500A includes a permanentmagnet 4502A embedded in the internal magnetic tool 4500A, which is usedto control the motion of the internal magnetic tool 4500A. The permanentmagnet 4502A may be made from a rare Earth material. The internalmagnetic tool 4500A may also include a blade 4504A that is shaped toperform a variety of cell manipulation functions. For example, the blade4504A may have a low-angle edge 4506A that is used to lift cells or cellsheets from the cell-bearing surface of the cell culture containerwithout damaging the cells. The blade 4504A may also have a high-angleedge 4508A that is used to lyse or detach cells. The blade 4504A mayalso have a tip 4510A that is used for precision lysing, detaching, orlifting of cells. In illustrative but non-limiting examples, a low-angleblade may form an angle at its cutting edge (i.e., the intersection ofthe two planar surfaces of the blade) that is no more than 1 degree, 2degrees, 3 degrees, 4 degrees, 5 degrees, 6 degrees, 7 degrees, 8degrees, 9 degrees, 10 degrees, 11 degrees, 12 degrees, 13 degrees, 14degrees, 15 degrees, 20 degrees, or 25 degrees. In illustrative butnon-limiting examples, a high-angle blade may form an angle at itscutting edge that is at least 25 degrees, 30 degrees, 35 degrees, 40degrees, 45 degrees, 50 degrees, 60 degrees, 70 degrees, 80 degrees, or90 degrees or more.

FIG. 45B illustrates another internal magnetic tool 4500B for use on acell-bearing surface in accordance with various implementations. Theinternal magnetic tool 4500B may be used for destructive removal ofcells in a cell culture and may have a compact footprint. The internalmagnetic tool 4500B may include a permanent magnet 4502B, embedded inthe internal magnetic tool 4500B, which is used to control the motion ofthe internal magnetic tool 4500B. The permanent magnet 4502B may be madefrom a rare Earth material. The internal magnetic tool 4500B may alsoinclude a circular blade 4504B. The internal magnetic tool 4500B mayrotate and translate along the plane of the cell-bearing surface to cutthrough portions of a cell culture.

The dimensions of the internal magnetic tools 4500A, 4500B may varydepending on the application. For example, in a liquid cell culturechamber there may be a relatively thin layer of liquid to achieve highcell media efficiency. The internal height of the chamber 4402 may be,for example, less than 2 mm, or less than 1 mm. In such a liquidchamber, the vertical height of the internal magnetic tools 4500A, 4500Amay be less than 1 mm, or less than 0.5 mm, or even less than 0.25 mm.Similarly, the maximum horizontal dimensions may vary, but will often beless than 2 mm, or even less than 1 mm, in order to allow editing oncell cultures where desirable cell features (such as colonies) arespaced a few mm apart or less. Internal magnetic tools contemplated inthis disclosure are not limited to those shown in FIGS. 45A-45B, but mayencompass any variation of shapes that achieve similar functionality.

FIG. 46A-C illustrate examples of cell editing functions provided by aninternal magnetic tool 4608 in accordance with various implementations.The internal magnetic tool 4608 may be similar to the internal magnetictool 4500A described with respect to FIG. 45A. The internal magnetictool 4608 may include a sharp tip 4610, a high-angle edge 4612, and alow-angle edge 4614.

In operation 4602, the internal magnetic tool 4608 may be translatedalong the plane of the cell-bearing surface with its sharp tip 4610forward to destroy or dislodge individual cells or small groups ofcells. The internal magnetic tool 4608 may also be rotated as it istranslated when destroying or dislodging cells.

In operation 4604, the internal magnetic tool 4608 may be rotated and/ortranslated along the plane of the cell-bearing surface such that itshigh-angle or blunt edge 4612 disrupts cells by detaching them from thecell-bearing surface and possibly rupturing their membranes. Generally,translating the high-angle edge 4612 of the tool into cells will havethe effect of destructively removing them from the cell-bearing surface.The detached cells may subsequently be removed from the chamber asdebris. This action may often be performed at higher velocities tomaximize the lysing effect and minimize editing time. The velocity ofmovement of the associated internal magnetic tool 4608 may be varied byvarying the magnetic force applied to it by the external magneticcomponent. If variable magnetic force is used in the system, the levelof force the internal magnetic tool 4608 applies towards thecell-bearing surface may be reduced in order to (i) reduce dynamicfriction force and allow faster tool motion; (ii) allow a slight gapbetween the internal magnetic tool 4608 and the cell-bearing surfacewhich may trap a portion of the cell and further ensure completemembrane destruction; and (iii) allow cells to be destroyed and removedwithout damaging the underlying cell growth matrix (such as Laminin orMatrigel), such that desirable cells may re-grow into the area.

In operation 4606, the internal magnetic tool 4608 may be translatedand/or rotated along the plane of the cell-bearing surface with thelow-angle or sharp edge 4614 leading to lift cells, groups of cells,colonies, or cell sheets intact from the cell-bearing surface. This maybe done at low velocity to minimize stress on cells. This operation mayalso be done with the highest magnetic down-force applied to theinternal magnetic tool 4608 by the external magnetic component in orderto have the closest contact between the internal magnetic tool 4608 andthe cell-bearing surface under the cells at the separation point. Insome implementations, the operation 4606 may be applied iteratively, inwhich a small section of the cells is lifted with each pass of thelow-angle edge 4614.

FIG. 47A illustrates cross-sectional views of examples of cell editingfunctions provided by an internal magnetic tool in accordance withvarious implementations. The cross-sectional views correspond to some ofthe cell editing functions illustrated in FIG. 46 . Specifically,cross-sectional view 4702A corresponds to operation 4604 and illustratesthe use of the high-angle edge 4612 of the internal magnetic tool 4608to remove cells from a cell-bearing surface. The internal magnetic tool4608 may be moved with relatively high velocity to destructively removecells. Cross-sectional view 4704 corresponds to operation 4606 andillustrates the use of the low-angle edge 4614 of the internal magnetictool 4608 to non-destructively remove cells from a cell-bearing surface.The internal magnetic tool 4608 may be moved with relatively lowvelocity to remove cells without destroying them.

FIG. 47B illustrates an example of cell editing functions provided by analternate internal magnetic tool 4702B in accordance with variousimplementations. The internal magnetic tool 4702B may be similar to theinternal magnetic tool 4500B illustrated in FIG. 45B. The internalmagnetic tool 4702 may be simultaneously translated and rotated alongthe cell-bearing surface to remove cells. For example, the internalmagnetic tool 4702B may include a number of blades that lyse and/or liftcells from the cell-bearing surface as the internal magnetic tool 4702Bis translated and rotated.

FIG. 48A-K illustrates cell editing operations conducted by an internalmagnetic tool 4802 during culturing of cell colony 4804 in accordancewith various implementations. The cell culturing process may beconducted by a cell culture system (e.g., system 110 in FIG. 1 ). Theinternal magnetic tool 4802 illustrated in FIG. 48 may be similar to theinternal magnetic tool 4500A in FIG. 45A. The cell colony 4804 may begrowing on a cell-bearing surface of a cell culture chamber and may havebeen selected for retrieval from the cell culture but may have someundesirable cells along its periphery. This may occur, for example, inan iPSC culturing process, in which cells along the edge of an iPSCcolony may begin to differentiate. It is important to remove these cellsbefore harvesting or transferring the cell colony.

In step (a) illustrated in FIG. 48A, the cell colony 4804 may be imagedby an imaging subsystem of the cell culture system (e.g., cell imagingsubsystem 112 in FIG. 1 ). In step (b) illustrated in FIG. 48B, acomputing subsystem of the cell culture system (e.g., computingsubsystem 110) may identify one or more undesirable cells in the cellcolony 4804, which are shown in gray. For example, the undesirable cellsmay be iPSC cells that have begun to differentiate in an iPSC cellcolony. A computing subsystem (e.g., computing subsystem 110) may usevarious machine learning and image analysis techniques on the image ofthe cell colony 4804 to identify the undesirable cells.

In step (c) illustrated in FIG. 48C, the computing subsystem maydetermine a path for the internal magnetic tool 4802 to follow to prunethe undesirable cells, the path shown by the solid line. The computingsubsystem may also determine various parameters for operating theinternal magnetic tool 4802, such as tool orientation, direction, andvelocity.

In step (d) illustrated in FIG. 48D, the computing subsystem mayactivate and control the internal magnetic tool 4802 to follow the pathaccording to the determined parameters to cut out and destroy theundesirable cells. For example, the computing subsystem may control anactuator connected to an external magnetic component that ismagnetically coupled to the internal magnetic tool 4802, and thuscontrol the path and parameters of the internal magnetic tool 4802. Theinternal magnetic tool 4802 may have a blade with a high-angle edge thatis used for lysing or destroying cells. The computing subsystem may alsoimage the internal magnetic tool 4802 and the cell colony 4804 in realtime and make dynamic changes to the path and parameters of the internalmagnetic tool 4802. For example, adjustments may need to be done toremove cells that weren't removed in a first pass, or to compensate forchanges or offsets to positioning.

Step (e) illustrated in FIG. 48E shows the cell colony 4804 afterpruning and ready for harvest. There may be several rounds of pruning(e.g., repeats of steps (a)-(d)) before the cell colony 4804 is readyfor harvest. In step (f) illustrated in FIG. 48F the computing subsystemmay determine a path for the internal magnetic tool 4802 to follow toharvest the cell colony 4804, the path shown by the solid line. Thecomputing subsystem may also determine various parameters for operatingthe internal magnetic tool 4802, such as tool orientation, direction,and velocity.

In step (g) illustrated in FIG. 48G, the computing subsystem mayactivate and control the internal magnetic tool 4802 to follow the pathaccording to the determined parameters to harvest the cell colony 4804.For example, the internal magnetic tool 4802 may have a blade with alow-angle edge that is used for incremental lifting, and that edgeapproaches the cell colony 4804 to slowly dig under the cell colony 4804and lift the cells off the cell-bearing surface. The internal magnetictool 4802 may be moved at a low velocity with maximum magnetic downforceso as to not damage the cells during the lifting process. The computingsubsystem may also image the internal magnetic tool 4802 and the cellcolony 4804 in real time and make dynamic changes to the path andparameters of the internal magnetic tool 4802. For example, adjustmentsmay need to be done to lift cells that weren't lifted in a first pass,or to compensate for changes or offsets to positioning, or if internalmagnetic tool 4802 is accidentally destroying cells.

Steps (h)-(j) illustrated in FIGS. 48H-48J, respectively, show thecontinuation of the lifting process. For example, the internal magnetictool 4802 may move in a spiral motion around the cell colony 4804,moving closer to the center with each pass. In step (k) illustrated inFIG. 48K, the lift-off process is complete and the fully-detached cellcolony 4804 is ready for harvest. The computing subsystem may, forexample, flush the cell colony 4804 out of the cell culture chamber intoanother receptacle. In other implementations, a mechanical tool may beused to push the cell colony 4804 out of the chamber, or gravity may beused as well.

FIG. 49A-I illustrates cross-sectional views of cell editing operationsconducted by an internal magnetic tool 4902 during culturing of cellcolony 4904 in accordance with various implementations. The cell editingoperations shown in FIG. 49 may be similar to the operations shown inFIG. 48 , namely removal of undesirable cells from the cell colony 4904and harvesting of the cell colony 4904. The cell culturing process maybe conducted by a cell culture system (e.g., system 110 in FIG. 1 ). Theinternal magnetic tool 4902 illustrated in FIG. 49 may be similar to theinternal magnetic tool 4A00A in FIG. 45A. The cell colony 4904 may begrowing on a cell-bearing surface of a cell culture chamber and may havebeen selected for retrieval from the cell culture but may have someundesirable cells along its periphery. The cell culture chamber may beliquid-filled, with an adherent cell culture on the upper inside surface(the cell-bearing surface) so that the force of gravity acts downward inFIG. 49 .

Step (a) illustrated in FIG. 49A shows the cell colony 4904 incross-section, with undesirable cells on the periphery marked in gray.An imaging subsystem (e.g., cell imaging subsystem 112) may have imagedthe cell colony 4904 and a computing subsystem (e.g., computingsubsystem 110) may use various machine learning and image analysistechniques to identify the undesirable cells.

In step (b) illustrated in FIG. 49B, the computing subsystem may controlthe internal magnetic tool 4902 via the external magnetic component 4906to remove the undesirable cells. For example, the computing subsystemmay determine a path for the internal magnetic tool 4902 to follow toprune the undesirable cells and also determine various parameters foroperating the internal magnetic tool 4902, such as tool orientation,direction, and velocity. Then the computing subsystem may activate andcontrol the internal magnetic tool 4902 to follow the path according tothe determined parameters to cut out and destroy the undesirable cells.The internal magnetic tool 4902 may have a blade with a high-angle edgethat is used for lysing or destroying cells. The computing subsystem mayalso image the internal magnetic tool 4902 and the cell colony 4904 inreal time and make dynamic changes to the path and parameters of theinternal magnetic tool 4902. The resulting cell debris from the pruningmay drop towards the bottom inside surface of the cell culture chamber.

In step (c) illustrated in FIG. 49C, the cell debris may be removed fromthe cell culture chamber via media flow or some other approaches, whichmay include but are not limited to use of magnetic tools (as disclosedherein) and/or gravity assistance (e.g., tilting or tipping containerappropriately). Step (d) illustrated in FIG. 49D shows the now-prunedcell colony 4904 on the cell-bearing surface. Sometime later, in step(e) illustrated in FIG. 49E, the cell colony 4904 may be ready toharvest. For example, there may have been several rounds of pruning ofundesirable cells before the cell colony 4904 is ready for harvest(e.g., iterations of steps (a)-(d)).

In step (f) illustrated in FIG. 49F, the computing subsystem maydetermine a path for the internal magnetic tool 4902 to follow toharvest the cell colony 4904, and also determine various parameters foroperating the internal magnetic tool 4902, such as tool orientation,direction, and velocity. The computing subsystem may activate andcontrol the internal magnetic tool 4902 via the external magneticcomponent 4906 to follow the path according to the determined parametersto harvest the cell colony 4904. For example, the internal magnetic tool4902 may have a blade with a low-angle edge that is used for incrementallifting, and that edge approaches the cell colony 4904 to slowly digunder the cell colony 4904 and lift the cells off the cell-bearingsurface. The internal magnetic tool 4902 may be moved at a low velocitywith maximum magnetic downforce so as to not damage the cells during thelifting process. The computing subsystem may also image the internalmagnetic tool 4902 and the cell colony 4904 in real time and makedynamic changes to the path and parameters of the internal magnetic tool4902.

Steps (g)-(h) illustrated in illustrated in FIG. 49G-H show thecontinuation of the lifting process. For example, the internal magnetictool 4902 may move in a spiral motion around the cell colony 4904,moving closer to the center with each pass. In step (i) illustrated inFIG. 491 , the lift-off process is complete and the fully-detached cellcolony 4904 has floated to the inner bottom surface of the cell culturechamber, where it may be harvested. The computing subsystem may, forexample, flush the cell colony 4904 out of the cell culture chamber intoanother receptacle. In other implementations, a mechanical tool may beused to push the cell colony 4904 out of the chamber, or gravity may beused as well.

FIGS. 50A-B illustrate an alternate implementation of an internalmagnetic tool 5000 in accordance with various implementations. Theinternal magnetic tool 5000 may be a two-ended tool that includes anembedded permanent magnet 5002, a sharp end 5004 used for precision celldestruction/lysing, and a flexible “scoop” or paddle end 5006 used fordetaching cell sheets or colonies (the flexible joint indicated bydotted line). The length of the internal magnetic tool 5000 may bedetermined by the internal cell culture chamber height and the desiredangle of the tool with respect to the surfaces of the cell culturechamber. For example, in a chamber with an internal height of 0.5 mm, atool with length 0.75-1.0 mm may be employed.

The internal magnetic tool 5000 may be guided by external magneticcomponents on both sides of the cell culture chamber, as opposed to asingle side. One advantage of this arrangement is that the contactregion of the internal magnetic tool 5000 with the inside surfaces ofthe cell culture chamber may be made very small (e.g., smaller than thefootprint of internal magnetic tools 4500A and 4500B), and thereforecell culture editing may be much more precise. A further potentialadvantage is that tools may be flipped while within the cell culturechamber. For example, by flipping the poles of the external magneticcomponents, the ends of the internal magnetic tool 5000 resident on eachsurface may be alternated, so that the sharp end 5004 and the flexibleend may be applied to either inner surface. A further potentialadvantage is that the internal magnetic tool 5000 may be disengagedeasily from the cell surface in order to form discontinuous tool paths,as described further herein.

FIG. 50A illustrates the use of the internal magnetic tool 5000 for cellremoval. The internal magnetic tool 5000 may be located in cell culturechamber 5008 having an upper cell-bearing surface 5014 and a lowersurface 5018. A cell colony 5010 is adhered to the cell-bearing surface5014. The internal magnetic tool is magnetically coupled to two externalmagnetic components: external magnetic component 5012 is located on theoutside of the cell-bearing surface 5014 while external magneticcomponent 5016 is located on the outside of the lower surface 5018. Theexternal magnetic components 5012, 5016 may be connected to actuatorscontrolled by a computing subsystem of a cell culture system (e.g.,system 110 in FIG. 1 ). The sharp end 5004 of the internal magnetic tool5000 may be pointed towards the cell-bearing surface 5014 while theflexible end 5006 may be pointed towards the lower surface 5018. Theexternal magnetic components 5012, 5016 translate along the cell-bearingsurface 5014 and the lower surface 5018 respectively. The externalmagnetic component 5012 may control the tool tip location and rotation(e.g., pointing angle) of the sharp end 5004 while the external magneticcomponent 5016 may control the tool tip location and rotation of theflexible end 5006. The sharp end 5004 may be used for lysing of cellsfrom the cell colony 5010 while the flexible end 5006 may be used forlifting cells from the cell-bearing surface 5014. This configurationallows highly precise editing of the cell colony 5010.

In some implementations the distance between the external magneticcomponents 5012, 5016 and the surfaces 5014, 5018 may be controlled,allowing for variation of the magnetic force between the externalmagnetic components 5012, 5016 and the internal magnetic tool 5000. Thisallows for varying the force applied by the tool tip to the surfaces5014, 5018 which may be useful for multiple functions. For example,lysing a cell may require more force than lifting a cell from thecell-bearing surface 5012. Also, if the magnetic force is weakened to acertain point the internal magnetic tool 5000 may lose contact with thesurfaces 5014, 5018 but may still be controllable by the externalmagnetic components 5012, 5016. This allows discontinuous tool paths byhaving the internal magnetic tool 5000 disengage from a surface at onepoint, float through the interior of the cell culture chamber 5010, andre-engage the surface at another point. In alternate implementations,the polarity of the external magnetic components 5012, 5016 may beswitched in order to push the corresponding tool tip away such that itdisengages from the surface, and then switched again when the tool tipshould be re-engaged.

FIG. 50B illustrates the capability of flipping the internal magnetictool 5000 within the cell culture chamber 5010. In diagram (b), thepolarity of both external magnetic components 5012, 5016 have beenswitched such that the internal magnetic tool 5000 flips orientationinside the cell culture chamber 5010 with respect to the orientationshown in diagram (a). After flipping, the external magnetic component5012 may control the tool tip location and rotation of the flexible end5006 while the external magnetic component 5016 may control the tool tiplocation and rotation of the sharp end 5004. In this configuration, theflexible end 5006 may be used to lift the cell colony 5010 from thecell-bearing surface 5014 by translating and/or rotating the internalmagnetic tool 5000.

FIG. 50C illustrates an exemplary 2-sided magnetic tool, with actuatorson both sides of a cell culture chamber, for the purpose ofsimultaneously controlling the position and tip orientation of a toolfor cell culture editing. The prototype is shown in a Corning CELLSTACKadherent cell culture vessel which has a growth area of about 636 cm²and a chamber height of about 17 mm.

Ultrasound Cell Editing Methods

In many adherent or semi-adherent cell culture processes it may bedesirable to selectively lyse cells or regions of cells to control thedevelopment of the cell culture. For example, cell lysis may be used toremove cells of the wrong phenotype, to isolate cells or colonies forthe purpose of having a clonal cell colony, to lyse and remove cells forthe purpose of controlling cell density and confluence, or toselectively lyse cells for the purpose of removing the respectivecellular components and contents for downstream analysis.

However, it may be challenging to design a cell editing system andmethod for use in a cell culture system. For example, any such cellediting approach may have to satisfy several requirements, including (a)selective lysing and removal of cells from a cell culture in a mannercompatible with automation, such that cells may be lysed according toimage or image time series characteristics that have been acquired usingan imaging system, (b) utilizing images to spatially select cells forlysing, and (c) doing so in a non-invasive manner such that the cellculture container does not need to be opened during the cell editingprocess.

Several approaches for cell editing in a cell culture system includelaser-based systems (including a configuration where laser pulses strikean absorbing coating proximate to the targeted cells) and a pass-throughmagnetic tool system in which a magnetic tool resides inside of the cellculture vessel for the duration of the process, and is actuated by useof external magnetic fields. However, additional cell editing approachesare also contemplated in this disclosure.

One alternate approach disclosed herein uses an imaging system toacquire images of an adherent or semi-adherent cell culture through thecell culture container surface, and then uses targeted focusedultrasound transmitted through the cell culture container wall andfocused spatially on specific cells, cell regions, or cell colonies inorder to selectively lyse them. Cell lysis by ultrasound is a well-knowntechnique and is applied to bulk volumes of cells in suspension.Typically, a transducer is inserted into an open container withsuspended cells, and emits ultrasonic pressure waves to “sonicate” thesuspended cells, breaking their membranes. Focused ultrasound has alsobeen used in vivo to disrupt cells, such as high intensity focusedultrasound (HIFU) which may be used for prostate cancer treatment.However, in these procedures the mechanism is largely thermal shockrather than mechanical lysing of cells.

The systems and methods disclosed herein for ultrasound cell lysing mayinclude a cell culture container for adherent or semi-adherent cells,the cell culture container configured to enable label-free imaging ofthe contained cells, an imaging subsystem that images cells through awall of the cell culture container, a computing subsystem that processesthe images of the cell culture and classifies cells, cell regions orcell colonies, a focused ultrasound system that acts through the wall ofthe cell culture container to selectively lyse cells according to theclassifications provided by the computing subsystem, and a method toremove the material generated by cell lysis. The focused ultrasoundsubsystem disclosed herein may also include, but is not limited to,electronically-driven spherical transducers, laser-generated focusedultrasound using a spherical absorbing/transducing surface, and phasedarray transducers.

The cell culture container (e.g., cell culture container 104 in FIG. 1 )may be a microwell plate, a cell culture flask, a microfluidic chamber,or other type of container used for cell culture processes. The cellculture container may be fully sealed for sterile processing of cells,for example a cell culture chamber attached to a tubing system forsupplying media and reagents and harvesting cell products (and celldebris). For the purposes of enhancing the ultrasound effect on thecells, to maximize cell lysis, microbubbles may be added to the cellculture prior to selective lysis. These microbubbles are used inultrasound imaging in order to enhance contrast, and may be gas sealedin stable shells. An example of this microbubble material is SonoVue®from Bracco Diagnostics, which includes a suspension of phospholipidshells filled with sulfur hexafluoride gas with diameters of 2-9microns.

FIGS. 51A-C illustrates ultrasound lysis of cells in a cell culturesystem in accordance with various implementations. FIG. 51A depicts acell culture surface 5100 of a cell culture chamber. Inside the cellculture chamber there is fluid media 5102 and an adherent cell culture5104. The cell culture surface 5100 may be transparent and configured tosupport the cell culture 5104. The transparency allows imaging of thecells using an imaging subsystem 5106, which may be similar to theimaging subsystem 112 in FIG. 1 . The imaging modality used by theimaging subsystem 5106 may include label-free imaging as well asfluorescently-labelled imaging. The images from the imaging subsystem5106 may be processed by a computing subsystem (e.g., computingsubsystem 110), and the cells in the cell culture 5104 are classified bythe computing subsystem.

FIG. 51B depicts a focused ultrasound transducer 5108 that iselectrically driven through a feed 5110. The electronic signal iscontrolled via a computing subsystem according to the position of thetransducer 5108 relative to the cell culture 5104, and theclassifications of the cells, to lyse specific cells or cell regions. Acoupling fluid (or gel) 5112 is used to enabled ultrasound transmissioninto the cell culture surface 5100 and towards the adherent cell culture5104. In some cases, the coupling fluid 5112 may double as immersion oilfor a microscope objective used by the imaging subsystem 5106 toincrease the imaging resolution of the imaging subsystem 5106. Generatedultrasonic waves 5114 pass through the coupling liquid 5112, through thecell culture surface 5100, and are focused on a region of the adherentcell culture 5104, resulting in the targeted lysis of local cells 5116.

FIG. 51C shows the cell culture 5104 after lysis and cell debrisremoval, with the targeted cells removed as indicated by the empty space5118. Cell debris may be removed by pipetting in the case of an opencell culture container, or by flow methods in a closed container orliquid chamber. The debris may be directed towards a waste container orbag (in the case of a sealed/closed liquid system), or towards acollection container or sample bag if the lysis products will be usedfor analysis.

FIG. 52A illustrates an alternate method (phased-array ultrasoundtransducer) of ultrasound lysis of cells in a cell culture system inaccordance with various implementations. In this implementation, ratherthan using a shaped surface, ultrasound is focused by use of an array oftransducers 5202A, each of which has a settable delay in signal emission(one-time settable using delay lines, or a programmable delay) to form afocused beam out of the combination of emitted signals. An advantage ofthis configuration is that it may be compact, but even more so that itcan allow high-speed steering (in the case of a fully-programmablearray) of the focus point across cell culture surface 5200A. A couplingfluid 5204A allows efficient transmission of the resulting ultrasonicsignal 5206A into the cell culture surface 5200A and towards a focuspoint 5208A where cells are lysed.

FIG. 52B illustrates a combined imaging and ultrasound lysing system ina cell culture system in accordance with various implementations. Theimaging subsystem and ultrasonic transducer may be combined into asingle head that can be translated relative to the cell culture forimaging as well as targeted cell lysing. In this example, an aperture5202B in an ultrasound transducer 5204B allows an imaging subsystem5206B (e.g., cell imaging subsystem 112) to image the cell cultureand/or to establish precise location of the ultrasound transducer 5204Brelative to prior images of the cell culture. A computing subsystem5208B (e.g., computing subsystem 110) then directs ultrasound drivers5210B based on the computed location and cell/cell regionclassifications, causing targeted lysis on the cell culture surface.

Washing Systems for a Closed Cell Culture Chamber

Adherent cell cultures grown in a cell culture chamber may requireoccasional washing for several purposes. For example, washing may beperformed to remove weakly adherent or non-adherent cells from the cellculture, remove adherent cells from the cell culture container intactfor the purpose of harvesting the cells, or remove cell debris from thecell culture. The cell debris may be weakly adherent to the cell culturecontainer or live cells. Cell debris may be present in the cell culturechamber after cell editing, in which selected cells are damaged or lysedthrough a number of methods, including but not limited to laser-basedcell damage or lysis, ultrasonic cell lysis, or mechanical cell lysis bya tool in the cell chamber.

In open cell culture containers such as microwell plates, petri dishes,and flasks, the washing process may be performed in a number of ways,including using a pipette or other liquid handling device to flush thecell-bearing surface with liquid, thereby dislodging cells or celldebris, or using tilting, rocking, or spinning of the cell culturecontainer to agitate the liquid. However, in closed cell culturechambers, the use of a pipette or similar device to flush the cellsurface is not possible. Furthermore, in closed cell culture chambers inwhich the chamber is substantially filled with liquid (e.g., amicrofluidic or millifluidic chamber), rocking or tilting the cellculture chamber has no effect due to the lack of a liquid-gas interfaceor any compressibility.

The primary methods used for washing cells in closed cell culturechambers in the prior art include repeated tilting of the chamber toinduce liquid flow or “sloshing,” in cases in which there is agas-liquid interface on the interior of the chamber. This method onlyworks when there is a gas-liquid interface, but may produce very unevenresults. Prior art solutions also include increasing the liquid flowrate and/or changing liquid flow direction in cases in which the cellculture chamber is completely liquid-filled. This method relies onhaving a pump that can produce sufficiently high flow rates within thecell culture chamber (which typically has a large cross-section comparedto the tubing) to induce shear stress on cells or cell debris. However,because of the typical geometries of cell growth chambers, this flow mayproduce very different shear conditions in different regions,potentially leading to uneven clearing of material and/or reduced cellviability.

Another washing method includes using higher levels of chemicaldissociation agents (e.g., enzymes such as Trypsin or recombinantreplacements), or longer exposure periods to these agents, to loosencell-cell and cell-container bonds. However, prolonged exposure to highconcentration of these agents reduces cell viability or induces celldeath. For these reasons it would be beneficial to have better systemsthat are applicable to closed adherent cell growth chambers,particularly liquid-filled ones, that enable better non-chemicalapproaches (or more lightly chemically assisted approaches) for washingcell cultures to remove debris and/or cells. Thus better ways ofperforming the washing process inside sealed, liquid-filled cell culturechambers are needed in the art, as such chambers are used to performhigh-volume, precision adherent cell culture processes, particularlywithin a cell culture system.

The systems and methods disclosed herein include several systems fortransmitting mechanical force from external actuators through the wallsof a sealed, liquid filled cell culture chamber to induce local orglobal liquid flows that act on adherent or semi-adherent cells or celldebris to separate them from the cell culture-bearing surfaces (ornon-cell culture bearing surfaces). The cells or cell debris may besubsequently removed from the cell culture chamber via liquid flow.

One implementation contemplated herein includes a mechanical actuatorthat pushes against a flexible or semi-flexible wall of a cell culturechamber to constrict a flow path locally, followed by a liquid flow tocreate a high-velocity flow over the cell culture in the area of theconstriction. This high-velocity flow creates shear stresses that detachcells or cell debris from a cell culture-bearing surface inside the cellculture chamber.

Another implementation contemplated herein includes a mechanicalactuator that pushes against a flexible or semi-flexible wall of thecell culture chamber to separate two or more regions of the cell culturechamber with one or more constrictions. The actuator may subsequently bemoved over the flexible surface to induce flow through the constrictionsfrom one set of regions to another set of regions, in which theresulting high-velocity flow creates shear stress to detach cells orcell debris from a cell culture-bearing surface.

Another implementation contemplated herein includes a mechanicalactuator that locally deflects a flexible or semi-flexible wall of acell culture chamber. As the wall is deflected by the mechanicalactuator, liquid moves out of the constricted region of the cell culturechamber due to the reduction in volume, causing a high-velocity flow(e.g., in a radial pattern) out of the constricted region under theactuator, and then back into the region as the actuator is moved awayfrom the chamber well. This motion may be repeated, causing a back andforth flow that applies shear stress to detach cells or cell debris froma cell culture-bearing surface.

Another implementation contemplated herein includes an ultrasonictransducer that is mechanically coupled to one surface of the cellculture chamber and transmits ultrasonic waves through the surface toinduce mechanical stresses on the cell culture surface and loosen cellsand/or cell debris.

Another implementation contemplated herein includes one or moreultrasonic actuators coupled to a cell culture chamber wall. Theultrasonic actuators create acoustic waves that travel along the wall ofthe cell culture container. The waves induce local motion in thecontainer wall that in turn create micro-flows within the cell culturechamber, which create shear forces on the cell-bearing surface to detachcells or cell debris.

Unlike the prior art, the implementations disclosed herein enablewashing of cells and cell debris from an adherent culture in a sealedcell culture vessel, including liquid-filled chambers, without breakingthe seal of the chamber or the supporting liquid systems. This approachmaintains sterility of the chamber, and also allows multiple cellculture chambers to be processed in a common environment without thepossibility of cross-contamination. It also enables cell culture washingwith high local liquid velocities and resulting shear stresses withoutrequiring a liquid and pumping system that by itself can create thesevelocities in the cell culture chamber. It potentially allows cellharvest or debris removal from 2D adherent cell cultures to be performedwith less chemicals or enzymatic dissociation agents (as well as lessexposure time to these agents), resulting in healthier cell cultures orproducts.

FIGS. 53A-B illustrate a mechanical method of washing away cells andcell debris from a closed cell culture chamber in accordance withvarious implementations. FIG. 53A illustrates a cell culture chamber5302 with an adherent cell culture growing inside. The cell culturechamber 5302 may be in a cell culture container (e.g., cell culturecontainer 104 in FIG. 1 ) of a cell culture system. A cell media-filledcavity 5304 is contained between walls 5306 and 5308. An adherent orsemi-adherent cell culture 5310 is adhered to the inside of the wall5306 (e.g., the upper wall). Both walls 5306, 5308 may be suitable forimaging and/or directed energy editing of the cell culture 5310. Mediain the cell culture chamber 5302 may be replenished by slow flow orstopped flow that also removes cell waste products. Dissolved gas (02for example) may be supplied as part of the fresh media feed, or througha gas-permeable surface. For example, wall 5308 may be a polymer wallthat is mechanically flexible and also gas-permeable.

In FIG. 53B, an actuator 5312 is pushed against a flexible wall of thecell culture chamber 5302, for example the wall 5308, in a specificregion of the cell culture chamber 5302. The wall may be pushed inwardsto decrease the wall-to-wall spacing within the fluid cavity, creating aconstricted region 5314 of the cell culture chamber 5302. Using a mediapumping subsystem inherent to a cell culture container containing thecell culture chamber 5302, media may be pumped through the cell culturechamber 5302. In the constricted region 5314, this results in ahigh-velocity and/or turbulent flow 5316 which creates sufficient shearstress on cells or cell debris to dislodge them from the cell culturesurface (e.g., inside of wall 5306), and pull them into the flow 5316.

In some implementations, liquid pumping may be performed in bothdirections, for example in back-and-forth flow switching, to dislodgematerial as desired without net use of cell media. The process may berepeated with the constriction at multiple locations within the cellculture chamber 5302. For example, the actuator 5312 may be a rollerthat pushes against the chamber wall and then slowly traverses the cellculture chamber 5302 along the direction of flow, propagating theconstricted region 5314 along the cell culture chamber 5302 while theliquid is pumped back and forth to create rapid flows in the constrictedregion and dislodge cell material. In general, the liquid flow velocity,duration, and number of repetitions may be controlled and optimized toremove only objects of interest (for example, but not limited to, celldebris remaining adherent or semi-adherent after selective destructionof cells, intact adherent cells, with or without use of disassociationagents, intact semi-adherent cells, intact non-adherent cells, 3Doutgrowths of 2D adherent cell cultures, dead or non-viable cells,etc.). The actuator 5312 may be controlled by a computing subsystem(e.g., computing subsystem 110) of a cell culture system. In anotherimplementation, substantially the entire cell culture chamber 5302 maybe squeezed using an actuator to reduce flow cross-section across theentire cell culture area, and then apply pumping to the system,resulting in higher flow velocities (higher shear forces) and/or lowerliquid volume requirements during washing processes.

The dislodged cells and cell debris may then be washed out of the cellculture chamber 5302 through several approaches. One example may be tolower the volume of fluid media in the cell culture chamber 5302 so thatthe adherent cell culture 5310 on the upper wall 5306 is not submerged.The dislodged cells and cell debris may settle on the bottom wall 5308.The rate of flow of fresh fluid media through the cell culture chamber5302 may be increased so that the dislodged cells and cell debris may beflushed out of the cell culture chamber 5302.

In some implementations, there may be no high velocity flow 5316 appliedwithin the cell culture chamber 5302. The motion of the actuator 5312itself as it pushes inwards on the wall 5308 and then back out creates arapid fluid flow out of the constricted region 5314 during the pushingaction, and then a fluid flow back into the constricted region 5314 asthe actuator 5312 is retracted. This process may be used to create localflow velocities and resulting shear forces on cells or cell debris todislodge them from the growth surface, with the flow velocitiesdetermined by the actuator 5312 velocity. Multiple cycles of actuatormotion may be used to locally wash the cell culture 5310.

FIGS. 54A-B illustrate another mechanical method of washing away cellsand cell debris from a closed cell culture chamber in accordance withvarious implementations. FIG. 54A illustrates a cell culture chamber5402 with an adherent cell culture growing inside. The cell culturechamber 5402 may be in a cell culture container (e.g., cell culturecontainer 104 in FIG. 1 ) of a cell culture system. A cell media-filledcavity 5404 is contained between walls 5406 and 5408. An adherent orsemi-adherent cell culture 5410 is adhered to the inside of the wall5406 (e.g., the upper wall). Both walls 5406, 5408 may be suitable forimaging and/or directed energy editing of the cell culture 5410. Duringmechanical agitation, the cell culture chamber 5402 may be sealed toprevent liquid flow in/out of the chamber, as shown in FIG. 54A. Thismay be done with pinch valves in the liquid handling subsystem, forexample, or by physical sealing of the cell culture chamber 5402 duringthis process.

An actuator 5412 is placed against a flexible wall of the cell culturechamber (e.g., wall 5408) and applies a force perpendicular to the wall5408 to bend the chamber wall inwards and constrict the cavity at aconstricted region 5414. The actuator 5412 is then slid or rolled acrossthe cell culture chamber 5402 to propagate the constricted region 5414.Due to the incompressibility of the liquid media, this forces a flow5416 from one side of the constricted region 5414 to the other, with thevelocity of this flow controllable by the amount of constriction as wellas the speed of the actuator motion across the cell culture chamber5402. This flow creates a shear force on the cell-bearing surface andits contents, dislodging cells or cell debris which are subsequentlyfloating in the media. The actuator 5412 may be controlled by acomputing subsystem (e.g., computing subsystem 110) of a cell culturesystem.

FIG. 54B illustrates an alternate implementation of the approach shownin FIG. 54A, using two actuators rather than one. A first actuator 5418is pushed into the chamber wall to form a constriction in the cellculture chamber 5402, separating the chamber into two non-constrictedregions 5422 and 5424. A second actuator 5420 is then also pushed intothe chamber wall, deflecting it inwards and reducing available volume inone of the non-constricted regions 5422. This forces liquid through theconstriction at high velocity into the other non-constricted region5424, where the flexible chamber wall expands to accommodate theadditional volume. In general, any number of actuators may be used insuch a chamber configuration to create washing protocols with highspatial and temporal specificity.

The dislodged cells and cell debris may then be washed out of the cellculture chamber 5402 through several approaches. One example may be tolower the volume of fluid media in the cell culture chamber 5402 so thatthe adherent cell culture 5410 on the upper wall 5406 is not submerged.The dislodged cells and cell debris may settle on the bottom wall 5408.The rate of flow of fresh fluid media through the cell culture chamber5402 may be increased so that the dislodged cells and cell debris may beflushed out of the cell culture chamber 5402.

FIGS. 55A-B illustrate methods for dislodging cells and cell debris in aclosed cell culture chamber in accordance with various implementations.FIG. 55A illustrates a cell culture chamber 5502 with an adherent cellculture growing inside. The cell culture chamber 5502 may be in a cellculture container (e.g., cell culture container 104 in FIG. 1 ) of acell culture system. A cell media-filled cavity 5504 is containedbetween walls 5506 and 5508. An adherent or semi-adherent cell culture5510 is adhered to the inside of the wall 5506 (e.g., the upper wall).Both walls 5506, 5508 may be suitable for imaging and/or directed energyediting of the cell culture 5510.

A directed energy source 5512 is used to disrupt selected cells in thecell culture 5510, damaging them or lysing them. The directed energysource 5512 may apply energy towards an outer wall of the cell culturechamber 5502 (e.g., the outside of wall 5506) in a directionperpendicular to the plane of the wall. The directed energy source 5512may be directed towards specific parts of the cell culture 5510 based onimaging of the cell culture 5502 and calculations regarding the cellculture 5502 by a computing subsystem (e.g., computing subsystem 110).The calculations may include, for example, cell density calculations,cell phenotype classifications, clonal colony separation distances,and/or predictions of cell/colony/regional outcome in a cell cultureprocess. In other implementations, the directed energy source 5512 maytarget regions in a pattern (for example, to reduce overall celldensity), or target regions of the cell culture chamber 5502 that arenon-optimal for the target cell culture process. As a result of thisdirected energy cell targeting, some cell components may be ejected orfloat into media, while others may still be adherent or semi-adherentafter the energy application.

FIG. 55B depicts an implementation for detaching (cells or) cell debrisfrom the adherent culture in which the directed energy source is anacoustic transducer 5514. The acoustic transducer 5514 may be coupled tothe cell culture chamber wall using a coupling gel or fluid 5516 andacoustic/mechanical waves are transmitted perpendicular to the chamberwall. The acoustic transducer 5514 may be applied to either thecell-bearing wall of the cell culture chamber 5502, or the wall oppositethe cell-bearing wall. The acoustic waves cause mechanical oscillationof the wall in the affected region 5518, resulting local liquid flowsthat dislodge cell debris into the media. The acoustic transducer 5514may be controlled by a computing subsystem (e.g., computing subsystem110) of a cell culture system.

FIG. 56 illustrates another method for dislodging cells and cell debrisin a closed cell culture chamber in accordance with variousimplementations. FIG. 56 illustrates a cell culture chamber 5602 with anadherent cell culture growing inside. The cell culture chamber 5602 maybe in a cell culture container (e.g., cell culture container 104 in FIG.1 ) of a cell culture system. A cell media-filled cavity 5604 iscontained between walls 5606 and 5608. An adherent or semi-adherent cellculture 5610 is adhered to the inside of the wall 5606 (e.g., the upperwall). Both walls 5606, 5608 may be suitable for imaging and/or directedenergy editing of the cell culture 5610. Acoustic transducers 5612 arecoupled to one wall of the cell culture chamber 5612 (e.g., wall 5606).The acoustic transducers 5612 transmit acousto-mechanical waves 5614across the wall to cause local distortions 5616 of the wallperpendicular to the plane of the wall. The acoustic transducers 5612may be controlled by a computing subsystem (e.g., computing subsystem110) of a cell culture system.

The local changes in volume within the cell culture chamber 5602 causemicroflows 5618 over the cell-bearing surface on the wall 5606, withassociated shear forces on cells or cell debris that dislodge cells orcell debris into the media volume. Typically, a “standing wave” in thechamber wall will be induced by the acoustic transducers 5612, in whichat a particular frequency some sections of the wall will experience themaximum upwards and downwards displacement, while others points of thewall (“nodes”) will be relatively stationary. To uniformly treat thechamber, a series of frequencies may be employed by the acoustictransducers 5612. In some implementations, the acoustic transducers 5612may be translated across the surface of the wall. In alternateimplementations, one or more mechanical actuators may be pushed againstthe wall to change the effective resonances of the wall and change theresulting standing wave patterns. In alternate implementations, an arrayof acoustic transducers may be coordinated in frequency and amplitude totarget specific regions of the wall for maximum deflection. An exampleof such a multi-transducer system is described in Hudin, Charles et al.,“Localized Tactile Stimulation by Time-Reversal of Flexural Waves: CaseStudy With a Thin Sheet of Glass,” IEEE World Haptics Conference, April2013, which is hereby incorporated by reference in its entirety.

Methods for Controlling Cell Culture Systems

Current cell culture processes rely either on timed processes withoutobservation or, in some 2D cell culture processes, occasional imagingand largely human observation of the cell culture in order to monitorprogress, assess quality, and/or make “editing” decisions which arelargely carried out manually. Examples of how cell cultures may beedited include passaging cells when a certain density is reached,removing cells that are differentiating, or transferring colonies thathave the “correct” morphology as seen by a human observer.

There is a strong desire in the industry to automate cell cultureprocesses, and accordingly there has been development in imageprocessing techniques to attempt to replicate expert observations ofcell cultures. For example, a number of image processing systems havebeen demonstrated that assess iPSC colonies based on their overallmorphology, in order to guide decisions on colony selection. Thesesystems essentially replicate current human observations, which may bedone at a single point in time or at multiple timepoints but withoutcorrelating information between images. Decisions may be based on theoverall image (pixel data) of a cell colony, corresponding roughly toshape and density. These systems generally do not incorporate cell-leveldata or statistics, nor do they incorporate time series data orstatistics.

There are few, if any, models that relate cell-level and time-seriesstatistics to outcome data for cell culture processes (e.g.,reprogramming, differentiation, gene editing expansion). As a result,the ability to predict and control cell cultures is extremely limitedusing current image analysis techniques, even if appropriate feedbackcontrol measures are put into plate (for example, editing the cellculture with a mechanism capable of removing cells, or transferringcells or colonies). Even if large scale times-series data could becollected, the volume of data that may be generated would make datastorage and analysis difficult. Large-scale automated biologicalmanufacturing must address these issues to be economically viable.

The various implementations disclosed herein include systems and methodsfor efficiently collecting and analyzing data from a cell culture andutilizing the data to automate cell editing decisions on the cellculture. These systems and methods solve the shortcomings of the priorart and allow for dynamic, automated, easily expandable cell monitoringand editing. FIG. 57A is a block diagram of a computing subsystem in acell culture system 5700A in accordance with various implementations.The cell culture system 5700A may be similar to the cell culture system100 described with reference to FIG. 1 . For example, the cell culturesystem 5700A may include a cell culture 5704A in a cell culturecontainer 5706A that undergoes a cell culture process to produce outputcell products 5718A. The cell culture system 5700A may also includecomputing subsystem 5710A, cell imaging subsystem 5712A, and cellediting subsystem 5714A that collectively monitor and controls the cellculture process. Output cell product assays 5720A may be performed onthe output cell products 5718A.

The cell culture container 5706A may be configured to enable label-freeimaging access to the cell culture 5704A held within it. In an exampleimplementation, the cell culture container 5706A may include a 96-wellmicroplate with an imaging-compatible coverslip (glass, oroptical-quality polymer) that is used to contain a cell culture 5704A ofsomatic cells being reprogrammed to iPSCs through the use of episomalvectors expressing the Yamanaka factors.

The cell imaging subsystem 5712A may be configured to acquire label-freeimages of the cell culture 5704A over time (for example, every 24 hours,or in another example, at a rate equal to more than two times the celldoubling rate). The cell imaging subsystem 5712A may employ imagingmodes including but not limited to brightfield imaging, darkfieldimaging, phase contrast imaging, differential interference contrastimaging, quantitative phase imaging, Fourier Ptychographic imaging, orcombinations thereof. The cell imaging subsystem 5712A may acquiremultiple images over the cell culture, with those images subsequentlymerged into a single larger image. In some implementations, the cellimaging subsystem 5712A may acquire a Z stack of images, with the Zstack subsequently used to better determine cell locations and celldata. An example of a normalized brightfield z-stack image of a hiPSCcell culture is shown in FIG. 58A. In some implementations, the cellimaging subsystem 5712A may use programmable illumination to provideillumination at multiple modes, angles, and/or colors. The cell imagingsubsystem 5712A may employ CMOS, CCD, or other image sensors to captureimages. The sensors may be area sensors or line sensors.

An example implementation of cell imaging subsystem 5712A may include abroadband LED-based brightfield illuminator that is configured toilluminate the cell culture 5704A in the cell culture container 5706A.The brightfield illuminator may have a 10× microscope objective (NA=0.3)that is mounted on a Z translation stage and a 5-megapixel 12-bitmonochrome CMOS camera that is used to capture images of the cellculture at 3 Z levels near optimal focus for the cell culture 5704A (inthis example, at Z=−5 microns, Z=0, and Z=+5 microns).

The images acquired by the cell imaging subsystem 5712A are generally ofa resolution that at least allows the resolution of individual cells ornuclei within the cell culture. For example, for a 2D adherent cellculture, images may be acquired at a resolution equal to at leastseveral times lower than the mean cell nuclear diameter, or the meannuclear spacing, whichever is smaller. In an example implementation,when monitoring iPSC reprogramming from blood cells the nucleardiameters average around 9 microns, and mean nuclear spacing may becomeas low as 5 microns in very dense iPSC colonies. In this example, animaging resolution of approximately 2 microns or lower is desirable inorder to subsequently identify cell nuclei. In some implementations, theimaging resolution used to identify cells or cell components (e.g.,organelles) is no more than about 10 microns, about 9 microns, about 8microns, about 7 microns, about 6 microns, about 5 microns, about 4microns, about 3 microns, about 2 microns, about 1 microns, or lower. Insome implementations, the imaging resolution used to identify cellcolonies is no more than about 25 microns, about 20 microns, about 15microns, about 14 microns, about 13 microns, about 12 microns, about 11microns, about 10 microns, about 9 microns, about 8 microns, about 7microns, about 6 microns, about 5 microns, about 4 microns, about 3microns, about 2 microns, about 1 microns, or lower.

The cell imaging subsystem 5712A may transmit the resulting image datato the computing subsystem 5710A via electronic or optical methods,which may be wired or wireless. The computing subsystem 5710A mayinclude a number of software and/or hardware modules that perform theimage analysis and cell editing determinations. For example, all of thecomponents in the computing subsystem 5710A as illustrated in FIG. 57Amay be implemented as software applications or routines. In anotherexample, some of the components may be implemented in software whileothers may be implemented in hardware or a combination of software andhardware.

The computing subsystem 5710A may include an image normalizer 5702A thatis configured to normalize all the received cell culture images.Normalization may include removal of local image artifacts or lightingconditions. For example, in the case of non-uniformity in illuminationover a single image field, the image normalizer 5702A may remove thisnon-uniformity by means of bandpass filtering, local mean subtraction ordivision, or division by/reduction by a pre-measured image field. Inanother example, each image may be low-pass filtered to produce an imageof the local lighting, in which the cutoff frequency for this low-passis chosen to remove most or all cell-related features. Subsequently, inthis example, the original image is divided by the low-pass result,producing an image that has been normalized to remove effects from localillumination or light capture conditions.

An image stitcher 5704A may receive the normalized images and isconfigured to produce a contiguous image from multiple images of thecell culture 5704A. For example, a single well of a microwell plate mayrequire around 50 image frames to capture all areas of the cell culturewith sufficient resolution. The image stitcher 5704A re-assembles thesetiles into a single contiguous image for storage and subsequentprocessing. The resulting contiguous image may have dimensions beyond2-dimensional axes. Examples of other axes may include but are notlimited to Z axis (from multiple Z slice images), illumination orcapture color channel, illumination or capture angle and combinations tomake 3- or higher-dimensional data volumes.

An important consideration is the sheer data volume that may begenerated at the point. In a relatively simple example in which a singlewell of a 96-well microplate is imaged at 5 Z positions, with imagingperformed at 1 micron resolution and with an output format of 16 bits,the resulting data volume for a single imaging pass is roughly 50Megabytes. This results in almost 5 Gigabytes of data for a single passover the plate. Cell culture processes performed herein may last upwardsof 30 days, with images captured daily or more, so data volumes ofhundreds of Gigabytes are possible. This amount of data would beextremely difficult to analyze or model directly against the biologicalresults of the cell culture process. As a result, most currentapproaches have used only snapshots of image data for this purpose.However, this sampling or single-timepoint approach loses a vast portionof the potentially relevant data in the cell culture. The computingsubsystem 5710A includes a number of modules designed to distill thisdata into a much smaller amount of information that nonetheless capturesall the critical features of the cell culture 5704A.

For example, the computing subsystem 5710A may include a cell locator5706A that performs the first step towards transforming large volumes ofimaging data into a much more compact representation of the cell culture5704A. The cell locator 5706A may be configured to receive the stitchedimage of the cell culture 5704A and to first segment the images toidentify cells or nuclei, and then to extract their center coordinatesand potentially nuclear envelopes from the segmented image. The celllocator 5706A may utilize conventional image processing and/or neuralnetwork-type processing to perform these functions. In an example, imageinformation from five or more Z slices may first be combined into threeimages. These three images are then input, in tile form, into aconvolutional neural network that has been pre-trained with sets oflabel-free images and corresponding fluorescent nuclear-stained images.An example of a convolutional network architecture used for this task isU-Net. The network produces a single image corresponding to thepredicted corresponding nuclear fluorescence image. This image issubsequently thresholded, and watershed morphological image processingis used to determine the centroid of each nucleus, as well as thecorresponding nuclear envelope. As an example, FIG. 58B shows a outputof a deep learning neural network that has been trained to predictnuclear stains from brightfield z-stacks.

The cell location data generated by the cell locator 5706A may be storedin an instant cell features database 5708A. “Instant” in this case meanslocation data from a single imaging timepoint. The data stored in theinstant cell features database 5708A may include, for each cell, thecoordinates of the cell in the observed portion of the cell culture5704A and the time at which the data was obtained. It may also includeother data such as cell or nuclear envelope information, which mayeither be a polygon representing the envelope or a feature descriptionof the shape.

Additional cell features may be extracted and added to the instant cellfeatures database 5708A by one or more cell feature predictors 5710A.The cell feature predictors 5710A may make further predictions at thecell or regional level based on prior training. For example, the cellfeature predictors 5710A may be trained with a series of brightfieldimages together with corresponding fluorescently-labeled images stainingfor cell pluripotency, the images received from the image stitcher5704A. The cell feature predictors 5710A may then produce an image ofthis predicted fluorescence, and use the previously-extracted XYcoordinates for each cell to calculate the local mean “virtual”fluorescence, and add the resulting feature to the cell record in theinstant cell feature database 5708A. Other cell features may becalculated directly from the instant cell feature database 5708A andadded to the cell records for convenience (for example, a calculation ofthe local cell density at various scales).

The cell locator 5706A and cell feature predictor 5708A may utilize arange of processing algorithms including, but not limited to: predictivemodels for semantic segmentation trained with supervised, unsupervised,and semi-supervised methods based on learned representations derivedfrom morphological features by the application of deep learning models(e.g., multilayer perceptrons and convolutional neural networks,including fully-connected networks, such as Mask R-CNN, networks withexpansive-path/contractive-path architectures (such as U-Net), with andwithout residual connections, trained with a multiplicity of objectivefunctions (such as focal loss, cross-entropy loss, and mean square errorloss)), using various optimizers in sequence and/or in combination (suchas stochastic gradient descent with and without momentum, RMSProp,Adagrad, and Adam) with various learning rate schedules, and ensemblesof models trained with the foregoing methods, together withimage-processing algorithms for the generation of training examples forthe supervised and semi-supervised training regimes, as well asimage-based post-processing and refinement of the semantic segmentationmasks derived from the deep-learning models.

A colony locator 5712A may be configured to use the instant celllocations stored in the instant cell feature database 5708A to calculatethe bounds of colonies within the cell culture 5704A. A colony of cellsmay include any subset, cluster, or region of the cell culture 5704A.This process may be performed using local density calculations and mayalso use additional features extracted by cell feature predictors 5710A(for example, a prediction of pluripotency). The colony locator 5712Aestablishes the bounds of each colony, typically in the form of apolygon.

Each colony record is then stored in an instant colony features database5714A. Additional colony properties may be calculated using colonyfeature calculator(s) 5716A. For example, various statistics regardingthe cells contained in the colony may be determined or estimated,including count, density, mean virtual fluorescence predictions, andother measures. In addition, geometric features of the colony may becalculated from the cell locations and/or outline polygon.

As a time series of images is collected, a colony tracker 5718Aassociates successive instant colonies with one another, in order toproduce persistent records of colonies, which are stored in a trackedcolony features database 5722A. For example, the colony tracker 5718Amay determine that a cell colony that is at roughly the same locationbetween two time-series images is the same colony. The colony may thenbe assigned a number or some other indicator, and information about thecolony at each point in time may be associated with each other andstored together. The tracked colony features of a colony may include aseries of instant colonies in the instant colony features database5714A, such that a time-series of instant colony feature may bereconstructed. However, it may be desirable to pre-compute and store arange of features for tracked colonies, including centroid trajectory,cell count history, area history, shape factor history, etc. Thesefeatures, together with cell statistic features, may be calculated usingone or more tracked colony feature calculators 5722A, and added to theappropriate tracked colony record in the tracked colony featuresdatabase 5722A. FIGS. 58C-H provide an illustrative example ofbrightfield image z-stack slices of a hiPSC colony proliferating overabout 65 hours and the corresponding image with calculated polygonsdelineating determined colony areas.

The databases in the computing subsystem 5710A (e.g., the instant cellfeatures database 5708A, the instant colony features database 5714A, andthe tracked colony features database 5722A) may be relational in amanner that allows features to be traced back to their origin. In otherwords, tracked colonies are related to the instant colonies that makethem up, which are related to the instant cell features that composethem, which can be traced back to specific regions of pixels in theimage data.

At this point the vast volume of image time series data has been reducedto a small set of features per tracked colony. This allows a colonyoutcome predictor 5724A to operate efficiently, and importantly to betrained with a reasonably small dataset. The colony outcome predictor5724A is configured to use the tracked colony features in the trackedcolony features database 5722A to predict outcomes for the colony interms of phenotype, functionality, genotype, pluripotency, purity,proliferation rate or other product characteristics. The colony outcomepredictor 5724A may calculate a score for each colony, the scorerepresenting the likelihood that the colony is or will produce highquality cell output products 5718A. The colony outcome predictor 5724Amay be driven by a statistical cell outcome model 5726A that has beenoptimized with a set of tracked colony features from the tracked colonyfeatures database 5722A and corresponding output cell product assayresults 5728A, which are in turn generated for each output cell product5718A using output cell product assays 5720A. The colony outcomepredictor 5724A and statistical outcome model 5726A may use one of anumber of machine learning methods including, but not limited to,logistic and multinomial regression, ordinal logistic regression,support vector machines, classification and regression trees, randomforests, boosted trees, principal components analysis, independentcomponents analysis, k-means, hierarchical, density-based, andneighborhood-based clustering, autoregressive models, gaussian processfitting, hierarchical Bayesian models, probabilistic graphical models,methods from topological data analysis such as persistent homology, deeplearning models, including multilayer perceptron models and recursiveneural networks, reinforcement-based models such as genetic algorithmmodels and virtual ant colony methods, as well as ensembles and cascadesof these methods together with heuristics and rules-based methods topredict quantitative and qualitative colony outcomes based on theextracted features stored in the tracked colony database 5722A andoutput cell product assay results 5728A.

In the case where colonies or regions of cells should be removed fromthe cell culture 5704A in order to make space for cells/regions withhigher predicted scores and/or to ensure clonality of the product, acolony editor 5730A may be configured to select regions or colonies tobe removed from the cell culture 5710A. The colony editor 5730A maydrive the editing subsystem 5714A that is capable of removing cells,colonies or regions of cells. The colony editor 5730A may also terminatea cell culture in order to dispose of it or to harvest output cellproducts 5718A. In some implementations, the colony editor 5730A mayalso control various actuators or other controls (e.g., controls 116) tomanipulate other environmental parameters within the cell culturecontainer 5706A. For example, the colony editor 5730A may controlfunctions such as shifting reagents or changing parameters such astemperature, pH, 02, nutrients, and media feed rate. The result of thisediting operation should be that the net predicted score for the cellculture 5704A is raised, and/or space in the cell culture container5706A is opened for the remaining (predicted) higher-scoring cells.

FIG. 57B is a flow chart of a method 5700B of controlling a cell culturein accordance with various implementations. The method 5700B may beperformed by a computing subsystem of a cell culture system (e.g.,computing subsystem 110 in cell culture system 100). The method 5700Bmay also the cell culture system to automatically monitor and edit thecell culture during a cell culture process.

In block 5702B, the computing subsystem may receive a plurality ofimages of the cell culture in a cell culture container. The images maybe received from a cell imaging subsystem (e.g., cell imaging subsystem112) that collects the plurality of images. The plurality of images maycollectively image the cell culture. The cell imaging subsystem mayutilize one of a variety of imaging methods to capture the images,including brightfield imaging, phase imaging, darkfield imaging,transmission imaging, reflection imaging, quantitative phase imaging,holographic imaging, two-photon imaging, autofluorescence imaging,Fourier ptychographic imaging, defocus imaging or any otherimplementations known to persons of ordinary skill in the art. Beforeimage analysis of the plurality of images, the computing subsystem mayperform a number of preprocessing steps, as described with reference toblocks 5704B-5706B.

In block 5704B, the computing subsystem may normalize the plurality ofimages. Normalization may include removal of local image artifacts orother irrelevant lighting effects or conditions from the images in orderto obtain clear images of the cell culture.

In block 5706B, the computing subsystem may stitch together theplurality of images in order to form a single image of the cell culture.The stitched image may be 2D image of the cell culture, or may include3-dimensional aspects as well. Each of the plurality of images may beassociated with location data that may be used to stitch the imagestogether properly.

In block 5708B, the computing subsystem may locate a plurality of cellsin the stitched image. The stitched image may represent the state of thecell culture at a specific point in time. A variety of image processingand/or neural network-type processing may be used to locate theplurality of cells. The location of a cell may be represented ascoordinates of the nucleus or center of the cell, and may also includenuclear envelope information as well. A cell feature predictor may beutilized, which uses prior imaging data as well as training set datathat allows the computing subsystem to distinguish individual cells fromother cells and background images, and to determine a coordinaterepresenting the location of the cell. The cell feature predictor mayimprove over time as more data is analyzed so that the predictor becomesmore accurate.

In block 5710B, the location of the plurality of cells may be stored.For example, the location data may be stored in an instant cell featuredatabase which records the location of each cell at each instant of timeat which the plurality of images (and the resulting stitched image) arecollected.

In block 5712B, the computing subsystem may identify one or more cellcolonies in the stitched image. A cell colony may be any grouping,subset, or region of the cell culture. A colony feature calculator maybe utilized to distinguish cell colonies from each other and frombackground images. The colony feature calculator may utilize celllocation data, prior imaging data as well as training set data toaccurately identify distinct cell colonies within the stitched image. Acell colony may be defined by shape and location data, as well as otherdata conveying information about the cell colony.

In block 5714B, information about each cell colony may be stored. Forexample, the cell colony data may be stored in an instant colonyfeatures database which records the location and properties of each cellcolony at each instant of time at which the plurality of images (and theresulting stitched image) are collected.

In block 5716B, the computing subsystem may track the one or morecolonies over time. This may include iterating the steps in blocks5702B-5714B at a number of points in time in order to collecttime-series cell colony data. The computing subsystem may utilize atracked colony feature calculator to determine the cell colonies in theimages over time. All data associated with the same cell colonies may beassociated with each other in order to produce time-series data aboutthe growth and changes of the cells and cell colonies over time. Thetracked colony feature calculator may utilize instant colony featuredata, prior imaging data, and training set data to accurately identifythe same colonies over time.

In block 5718B, the times-series data about each tracked colony may bestored in a database. For example, the tracked cell colony data may bestored in a tracked colony features database which records the locationand properties of each cell colony over time.

In block 5720B, the computing subsystem may predict outcomes of eachtracked colony in the cell culture. For example, the computing subsystemmay generate an outcome score based on the time-series tracked cellcolony data. The outcome score may represent the likelihood that aparticular cell colony may successfully produce the desired output cellproduct at a future time. A cell outcome model may be utilized togenerate the outcome score. The outcome score may be based on a numberof data sources, including the time-series tracked colony data of thecurrent cell culture, tracked colony data from prior cell cultureprocesses of the same type, output cell product assay data, and trainingset data.

In block 5722B, the computing subsystem may edit one or more of thetracked colonies based on the predicted outcome for the trackedcolonies. For example, if an outcome score of a cell colony indicatesthat it is a low quality colony that is unlikely to produce the desiredoutput cell product, the computing subsystem may instruct a cell editingsubsystem (e.g., cell editing subsystem 114) to remove the low qualitycolony. In another example, the computing subsystem may determine thattwo cell colonies will soon overlap and instruct the cell editingsubsystem to remove the cell colony with a lower outcome score in orderto provide more space for the remaining cell colony to grow. Editing mayencompass other functions that effect cell colony growth, such astransferring cargo into and out of cells, or changing environmentalparameters of the cell culture container.

The method 5700B may repeat itself iteratively throughout the cellculture process until the output cell product is completely harvested,or the cell culture is disposed of in its entirety. In this manner, themethod 5700B provides automated and dynamic tracking, prediction, andcontrol of the cell culture process. This eliminates the need for manualhuman intervention and lessens the potential for contamination fromthese interventions, and also increases the speed at which cell culturesare processed. Finally, by reducing high density imaging data into lowdensity cell colony data, the method 5700B reduces the need to store,transfer, and analyze large quantities of data.

The computing system shown in FIG. 57A may be used to implement themethod shown in FIG. 57B in order to generate images such as those shownin FIGS. 58A-58H. FIG. 58A shows an exemplary normalized brightfieldz-stack image of a hiPSC. FIG. 58B shows an exemplary output of a deeplearning neural network that has been trained to predict nuclear stainsfrom brightfield z-stacks, after thresholding. FIG. 58C shows a firstexemplary brightfield image z-stack slice of a hiPSC colonyproliferating over about 65 hours. FIG. 58D shows the image of FIG. 58Awith polygons delineating determined colony areas. FIG. 58E shows asecond exemplary brightfield image z-stack slice of a hiPSC colonyproliferating over about 65 hours. FIG. 58F shows the image of FIG. 58Cwith polygons delineating determined colony areas. FIG. 58G shows athird exemplary brightfield image z-stack slice of a hiPSC colonyproliferating over about 65 hours. FIG. 58H shows the image of FIG. 58Ewith polygons delineating determined colony areas.

Unsupervised Attribute Classification

In many adherent or semi-adherent cell culture processes it is desirableto classify cells or regions of cells automatically to control thedevelopment of the cell culture. Once cells are classified according tovarious attributes, decisions may be made regarding the cell cultureprocess. For example, cells of the wrong phenotype or cells withundesirable mutations or behavioral patterns may be identified andremoved from the cell culture.

Such a classification system should have several capabilities tofunction within a cell culture system, particularly a system that isautomated. For example, the automated classification system should beable to extract visual data patterns from image or image timeseries datathat correlate to high quality cells or cell colonies. Measures of highquality may be defined based on biological quality control (QC) assaysand expert interpretation of such QC assay data in the context ofdesired biological processes (e.g., differentiation to iPSC cells,reprogramming of iPSC cells, or differentiation to dopaminergicneurons). High quality may also be defined based on cell staining/fixingand imaging cells in such labeled modalities that capture and highlighta desired property of the cell.

Correlations of image data to attribute classifications may be learnedin an offline manner from data collected for training purposes, or in anonline manner from data collected during cell manufacturing process, ora combination of offline learning and online continuous updates tolearned correlations. An automated classification system with onlineand/or offline learning should learn to map the visual data patternsacquired from label-free image or image timeseries data to data patternsacquired from biological QC assays and labeled-image data.

An automated classification system that is integrated into a cellculture system should be configured to extract the relevant visual datapatterns from label-free image or image timeseries data captured innon-invasive ways and without staining or fixing the cells. Theautomated classification system should also be configured to extract therelevant visual data patterns from label-free image or image timeseriesdata without the need for manual expert guidance or supervision such asannotation, labeling, or delineation of cells or regions of cells. Inaddition, a cell culture system utilizing an automated classificationsystem should be configured to control a submodule for selective lysingand removal of cells from a cell culture and carry out biological QCassay data collection based on the output of the online learning system.For example, the cell culture system may lyse cells in a spatiallyselective manner according to image or image time series characteristicsthat have been acquired using a cell imaging subsystem.

The automated classification system should also be configured to extractvisual data patterns from label-free image or image timeseries datawhich are relevant to the task of quality assessment of cells or cellcolonies or cell groups. Finally, the automated classification systemshould be configured to classify cells in a non-invasive manner suchthat the cell culture container does not need to be opened during theprocess.

The systems and methods disclosed herein provide ways of controlling acell culture system using an automated classification system withunsupervised learning and inference aspects. In unsupervised learning,relevant visual patterns of imaging data are discovered automaticallyfrom a large amount of data and no human supervision is required. Inthis framework, a large dataset of label-free images may be collected bythe imaging subsystem from many cell cultures of a given cell typeundergoing a particular biological process. An unsupervised learningengine may be configured to output visual categories that correspond toclusters of spatio-temporal features automatically discovered in thatdataset. These visual categories may be indicative of attributes or cellquality of the cell culture (e.g., dense or sparse cell growth, cellmorphology, cell division rate, cell motility). The visual categoriesmay be associated with one or more categories of cell quality attributesbased on expert interpretation of observed image patterns in members ofthe output visual categories or based on QC or labeled-image datacollected from the members of the output visual categories. Anunsupervised inference engine may then generate cell quality attributemaps that annotate the cell culture images automatically. Thisinformation may be used by the cell culture system to make decisionsabout altering cell culture parameters, destroying certain cells or cellregions, collecting additional cells and/or cell contents for assays ortesting, and other actions. The unsupervised learning engine for visualclassification may use one of a number of machine learning methodsincluding, but not limited to, principal component analysis,autoencoders, variational autoencoders, generative adversarial networksand deep metric learning.

The unsupervised classification system has several advantages over priorart solutions. For example, the unsupervised learning engine may beretrained relatively quickly when there are changes in the cell culturesystem's imaging protocols and/or hardware. If manualannotation/labeling were used, it would have to be repeated each timesystem protocols or hardware change. In addition, the unsupervisedsystem is capable of handling multiple imaging modalities, z-slices, ort-slices by changing the number of input channels and thereby increasingthe dimensionality of the input space to be encoded in an unsupervisedmanner. The amount of training data that the unsupervised learningengine utilizes increases substantially as the space dimension increasesand so there is a trade-off in configuring the input channels and thetraining data needs. However, an automated cell culture system cancollect large amounts of image data relatively quicker if manualannotation or supervision is not required to label each training sample.

Furthermore, the visual categories learned in unsupervised ways may beas granular as desired and the learning engine may be tuned to pick upon very subtle spatio-temporal differences in cell regions. Suchemerging categories may be mapped into colony/cell behavior attributesthat relate to desired/undesired aspects of the cell culture. Multiplevisual categories may be mapped to the same behavioral attribute and soover-categorization in the visual domain is harmless. In this way,subtle behavioral changes may be caught by the system that may otherwisenot be possible to catch through human observation of the imaging data.Previously unknown spatio-temporal patterns may also be discovered in acompletely automated and unsupervised manner.

Finally, unsupervised model parameters may be learned for each cell typeby collecting data from cultures of that cell type. Introducing a newcell type into the system would be relatively easy in the sense thatmanual annotations are not needed to categorize visual patterns fromthis new cell type. The system would train on label-free images of thenew cell type and have new emergent visual categories for the new celltype.

FIG. 59 is a block diagram of an automated classification system 5900 ina cell culture system in accordance with various implementations. Theautomated classification system 5900 may include different subsystems ofthe cell culture system such as an imaging subsystem (e.g., cell imagingsubsystem 112), a lysing or removal subsystem (e.g., cell editingsubsystem 114), and a computing subsystem (e.g., computing subsystem110). FIG. 59 illustrates the operation of the automated classificationsystem 5900 during the learning phase. One or more cell cultures 5902are cultured in the cell culture system. The cell cultures 5902 maycontain cells of the same cell type, and each cell culture 5902 mayinclude one or more cell colonies, regions, or groups. An imagingsubsystem of the automated classification system 5900 (e.g., cellimaging subsystem 112) may image the cell cultures 5902 to produce imagedata 5906. The image data 5906 may be label-free images of the cells,cell colonies, or cell regions.

An unsupervised learning engine 5908 may take the image data 5906 andproduce a plurality of visual categories 5910 (e.g., categories 1through M). The unsupervised learning engine 5908 may be part of thecomputing subsystem (e.g., computing subsystem 110). The unsupervisedlearning engine 5908 may identify similar visual features or patternsfrom the image data 5906 and generate visual categories 5910 for eachsimilar visual feature/pattern that appears throughout the image data5906. The visual categories 5910 may include, but is not limited to, lowintercellular spacing, high intercellular spacing, high density ofnucleoli, and cells at different stages of growth (e.g.,undifferentiated, differentiated), cells with different cell divisionrates, and cells with different phenotypes. Each cell type may havedifferent visual features, thus for each cell type there may be anassociated plurality of visual categories 5910. In unsupervisedlearning, the visual categories 5910 may be discovered automaticallyfrom the image data 5906 without human or other kinds of supervision.The image data 5906 may be divided into image patches of apre-determined size and each image patch may be passed through theunsupervised learning engine 5908 to train a classification model.

Cell colonies from each cell type present unique visual features thatcorrelate to desired or undesired growth and behavior for individualmembers or cell groups of that cell type. For example, researchers haveidentified several visual features that correlate to the typicalmorphology of healthy, undifferentiated iPSC colonies such as prominentnucleoli, less intercellular spacing, and no spontaneouslydifferentiated cells. Label-free images of iPSC colonies may berepresented as smaller image patches and each image patch may be broadlymanually labeled as good, moderate, or poor quality in terms of thevisual appearance of the cells in that image patch. Thus each visualcategory 5910 may be manually associated with one or more attributecategories that provide information about the attributes of the cells inthat visual category. The attribute categories may include qualityattributes (e.g., high quality, medium quality, low quality cells) orother attributes of cells or cell colonies/regions that may be relevantto cell culture process decisions (e.g., whether to remove certain cellsfrom a cell culture or extract cells for assay profiling).

The unsupervised learning engine 5908 may generate model parameters thatare passed to an unsupervised inference engine 5912. The unsupervisedinference engine 5912 may be part of the computing subsystem (e.g.,computing subsystem 110). The model parameters may include the visualcategories 5910 and associated attribute categories. The unsupervisedinference engine 5912 may take the model parameters and the image data5906 as input and generate labeled images annotated with the attributecategories. For example, the unsupervised inference engine 5912 mayidentify the visual categories 5910 within the image data 5906, identifyinstances of the visual categories 5910 within each image, and annotatethose sections of the image with the associated attribute category. Theoutput of the unsupervised inference engine 5912 may be attribute mapsof the cell cultures 5902, in which different cells and cellregion/colonies are labeled according to their attributes. This outputmay be used by the cell culture system to determine whether certaincells or cell regions/colonies should be edited (e.g., removed), toidentify cells that may be assayed for additional information, whetherparameters of the cell culture growth process should be changed, orother decisions.

FIG. 60 is a block diagram of components in an automated classificationsystem 6000 in accordance with various implementations. The automatedclassification system 6000 may be similar to the automatedclassification system 5900 in FIG. 59 and may include two main engines:an unsupervised learning engine 6002 and an unsupervised inferenceengine 6010. The unsupervised learning engine 6002 may include a patchgeneration module 6004, an autoencoder network training module 6006, andan unsupervised clustering module 6008. The unsupervised inferenceengine 6010 may include an encoding network module 6012 and a clusterassignment module 6014.

The patch generation module 6004 may be configured to receive label-freeimages and divide them into image patches. The size of the patch may bepredetermined (e.g., 64 pixels by 64 pixels), and it should be largeenough to capture sufficient visual feature patterns but small enough tolimit the input space dimension. The patch may have dimensions in the Xand Y planes (e.g., 2D image plane of the cell culture surface), but mayalso encompass the Z dimension (focus level) and T (timepoint), andwavelength cases where hyperspectral, Raman, autofluorescence, orfluorescently-labelled imaging is used.

The autoencoder network training module 6006 may be configured to learna low dimensional encoding space from the much higher dimensional inputimage patch space. Autoencoding networks are a class of algorithms inmachine learning that are used for various computer vision tasks todiscover latent state spaces that relate to the task. Variationalauto-encoders (VAEs) and Generative Adversarial Networks are two exampleneural network architectures that are commonly used. Similarly, thereare well established unsupervised clustering techniques such as k-meansor tSNE that may be applied to the data mapped to the encoding space tocreate visual clusters.

Cells at various states of the cell culture process may exhibit behaviorthat creates homogenous visual/temporal patterns among the cells of thesame state. This allows the autoencoder network training module 6006 toefficiently represent this state information as an abstraction over themuch higher dimensional image space. Cells which are in different states(e.g., one state may be desirable, such as having prominent or abundantnucleoli, but another state may be undesirable, such as largeinter-cellular spacing indicative of spontaneous differentiation) willexhibit different spatio-temporal patterns and would be encoded intodifferent portions of the encoding space. Autoencoders have the abilityto effectively discover such underlying abstractions or states indatasets and create very efficient (low-dimensional) encoding spaces.

In some implementations, each image patch may have multiple datachannels that correspond to various image modalities given by theimaging subsystem (e.g., z-slices or t-slices) and/or timeseries imagedata. Thus the number of input channels to autoencoders may be increasedto include timeseries images of the patch and thus enablespatio-temporal encoding of patches. Such spatio-temporal encoding maycapture cell stacking behavior, mobility, proliferation, and changecharacteristics in various portions of a cell colony, which maycorrelate with unhealthy growth, mutation, or non-clonal origin.

The unsupervised clustering module 6008 may be configured to applyunsupervised clustering (e.g., k-means) to the encoded features of thelower dimensional image patch data generated by the autoencoder networktraining module 6006 to identify visual categories. In other words, theunsupervised clustering module 6008 may identify similar visual featuresacross image data and classify those features into the same category. Byusing an unsupervised approach, a large number of visual patch classesmay be learned across many cell culture images and may reveal previouslyunknown visual patterns that correlate with various colony attributeindicators.

The visual categories generated by the unsupervised learning engine 6002may be associated with attribute categories through human intervention.For example, a person may review each visual category and assign one ormore cell quality attributes to the visual category. The attributes mayinclude healthy behavior measures or other attributes relevant todetermining the successfulness of the cell culture process. Additionalinformation may also be used to help associate visual categories withcell quality attribute categories. For example, assay profiles of theimaged cells or labeled images of the cells (e.g., via staining) mayprovide additional information for determining attributes of the cells.

The unsupervised inference engine 6010 may take as input the label-freeimages of the cell culture and product an output cell quality attributemap (i.e., labelled image). The encoding network module 6012 in theunsupervised inference engine 6010 may be configured to use modelparameters learned by the autoencoder network training module 6006during learning phase. The cluster assignment module 6014 may beconfigured to use the model parameters learned by the unsupervisedclustering module 6008 during the learning phase. The output of theunsupervised inference engine 6010 may be an attribute map or image ofthe cell culture that is annotated with the cell attribute categories inthe appropriate locations. The output may be used by the cell culturesystem to make cell editing, assay, and other cell culture processdecisions.

FIG. 61 is a block diagram of an automated classification system 6100learning to associate visual categories previously discovered by anunsupervised learning engine from label-free images to cell attributecategories by means of a cell lysing and assay methodology in accordancewith various implementations. The automated classification system 6100may include different subsystems of the cell culture system such as animaging subsystem (e.g., cell imaging subsystem 112), a cell lysing orremoval subsystem (e.g., cell editing subsystem 114), and a computingsubsystem (e.g., computing subsystem 110). FIG. 61 illustrates theoperation of the automated classification system 6100 during theattribute association phase being trained on QC assay data of samplescollected from each visual category. One or more cell cultures 6102 arecultured in the cell culture system. The cell cultures 6102 may containcells of the same cell type, and each cell culture 6102 may include oneor more cell colonies, regions, or groups. The cell culture system maybe configured to perform selective cell lysing and assay profilingfunctions 6104 (e.g., using the cell editing subsystem 114) of the cellcultures 6102 to acquire assay profile data 6108 of each visual category(e.g., categories 1 through M). For example, select cells may bedislodged and flushed from the cell cultures 6102 and assays areperformed on the extracted cells.

Specifically, an unsupervised inference engine 6116 initialized withmodel parameters learned by an unsupervised learning engine may take asinput label-free image data 6114 of the cell cultures 6102 and producelabeled visual category maps 6118. The labeled images 6118 may beprovided to a controller 6120 which determines the coordinates for cellsand cell regions/colonies expressing same visual categories. Thecontroller 6120 may control a cell editing subsystem (e.g., cell editingsubsystem 114) to selectively remove cells expressing same visualcategories from the cell cultures 6102, for lysing and assaying, orother cell culture processes. For example, for each visual category 6106the cell culture system may select a representative group of cells fromthe cell culture 6102 and lyse those cells and perform assays on them.In this way, a certain amount of assay profile data can be collected foreach visual category in 6106 that is statistically sufficient to runfurther analysis.

Given sufficient assay profile data from each visual category, asupervised learning engine 6110 may be utilized to associate cellcolony/region attribute categories 6112 to the visual categories 6106with the aid of human intervention. For example, a portion of the assayprofile data 6108 from all of the visual categories 6106 may be reviewedand categorized into attribute categories 6112 manually. This manuallyannotated subset may be used to train a classifier that learns to mapassay profile data 6108 to the attribute categories 6112. The attributecategories 6112 may include any number of desirable or undesirableattributes in the context of the cell culture process on the specificcell type. Once a classifier is trained, each assay data sample from agiven visual category 6106 may be classified and a consensus votingamong all sample data from this visual category may determine theassociation of that visual category to one of the attribute categories6112. Note that an off-the-shelf assay data classifier may be used bythis attribute learning method and/or the classifier does not need to betrained on the data collected via the procedure described herein.Furthermore, the classifier may also be a simple rule-based algorithmwhich operates based on pre-configured rules specified by biologyexperts, for example checking for expression of a certain protein morethan a specified quantity.

FIG. 62 is a block diagram showing an example association of visualcategories 6202 (1 through M categories) to attribute categories 6204 (1through N) in accordance with various implementations. This mapping maybe similar to the association performed by an automated classificationsystem when learning from label-free (FIG. 61 ) or labeled (FIG. 63 )image data. In other words, each visual category 6202, along with assayprofile information if available, may be mapped to one or more attributecategories 6204. This association may be supervised, i.e., done withhuman intervention. Note that a large number of visual categories may beassociated to only a few cell attribute categories (i.e., M>>N).

FIG. 63 is a block diagram of an automated classification system 6300learning the association of visual categories to cell attributecategories via selective staining and labeled imaging in accordance withvarious implementations. The automated classification system 6300 mayinclude different subsystems of the cell culture system such as animaging subsystem (e.g., cell imaging subsystem 112), a cell lysing andremoval subsystem (e.g., cell editing subsystem 114), and a computingsubsystem (e.g., computing subsystem 110). FIG. 63 illustrates theoperation of the automated classification system 6300 during theattribute association phase being trained on labeled image datacollected from samples of each visual category. One or more cellcultures 6302 are cultured in the cell culture system. The cell cultures6302 may contain cells of the same cell type, and each cell culture 6302may include one or more cell colonies, regions, or groups.

Specifically, an unsupervised inference engine 6316 initialized withmodel parameters learned by an unsupervised learning engine may take asinput label-free image data 6314 of the cell cultures 6302 and producelabeled visual category maps 6318. The labeled images 6318 may beprovided to a controller 6320 which determines the coordinates for cellsand cell regions/colonies expressing same visual categories. Thecontroller 6320 may control a cell staining and labeled imagingsubsystem (e.g., may be part of the cell imaging subsystem 112) toperform selective staining of cell cultures and labeled imaging 6304 ofthe cell cultures 6302 to acquire labeled images 6308. For example, foreach visual category 6306 the cell culture system may select arepresentative group of cells from the cell culture 6302, stain them,and then image the stained cells. In this way, a certain amount oflabeled image data can be collected for each visual category in 6306that is statistically sufficient to run further analysis.

A supervised learning engine 6310 may be configured to generate cellcolony/region attribute categories 6312 from the labeled images 6308with the aid of human intervention. For example, a portion of thelabeled images 6308 from all visual categories 6306 may be assigned toone of the cell attribute categories 6312 by experts manually. Theattribute categories 6312 may include any number of desirable orundesirable attributes in the context of the cell culture process on thespecific cell type. This subset of manually annotated data may be usedto train an image classifier that learns to map a label image into oneof the attribute categories 6312. Each labeled image sample from a givenvisual category 6306 may be classified and a consensus voting among allsample data from a visual category may determine the association of thatvisual category to an attribute category. In alternate implementations,the learning engine 6310 may be unsupervised after training based onlabeled images. Note that for the supervised learning engine 6310, ifavailable, an off-the-shelf image classifier that maps labeled images toattribute categories may be used if a standard staining andlabeled-image collection procedure is used for the biological process inquestion. Similarly, if appropriate, a simple rule-based classifier mayalso be configured for the supervised learning engine 6310 to measurethe existence of certain stains in a minimum number of pixels in thelabeled images.

FIG. 64 is a block diagram showing manufacturing of cells using anautomated classification system 6400 in accordance with variousimplementations. After the automated classification system 6400 hascompleted learning/training as described with reference to FIGS. 59-63 ,the automated classification system 6400 may be utilized in a cellmanufacturing process. The automated classification system 6400 may bepart of a cell culture system (e.g., cell culture system 100). A cellculture 6402 grown in a cell culture container (e.g., cell culturecontainer 104) may contain cells of a certain type. An imaging subsystem6404 (e.g., cell imaging subsystem 112) may collect image data 6406 ofthe cell culture 6402 during the growth process.

The image data 6406 is fed into an unsupervised inference engine 6408,along with model parameters 6410 generated by an automatedclassification system that has been trained as disclosed with referenceto FIGS. 59-63 . For example, the model parameters 6410 may includevisual categories for the cell type grown in the cell culture 6402 and,for each visual category, its associated attribute categories. Theunsupervised inference engine 6408 generates attribute maps 6412, whichmay be images of the cell culture 6402 in which cells or cellcolonies/regions are labeled with various attributes according to theirvisual characteristics as well as other information (e.g., informationobtained from assays or stained images). A colony management system 6414(e.g., computing subsystem 110) may utilize the attribute maps 6412 tomake decisions about cell culture processes like cell editing,additional selective cell lysing and assay profiling, and modifyingenvironmental parameters of the cell culture growth process. The colonymanagement system 6414 may generate instructions 6416 which are used tocontrol other components in the cell culture system (e.g., cell imagingsubsystem, cell editing subsystem, container sensors and controls).

FIG. 65 is a flow chart of a method 6500 of classifying image data in acell culture system in accordance with various implementations. Themethod 6500 may be performed by one or more components in a cell culturesystem (e.g., cell culture system 100), such as an automatedclassification system as disclosed with reference to FIGS. 59-63 . Themethod 6500 may be performed during the learning or training phase ofthe automated classification system.

In block 6502, the cell culture system grows one or more cell cultures.The cell cultures may be grown in cell culture containers (e.g., cellculture containers 106) and be of the same cell type. The cell culturecontainers may allow for label-free imaging and editing in a closedsystem (e.g., a closed cassette). In block 6504, the cell culture systemmay obtain image data of the one or more cell cultures. The image datamay be collected by a cell imaging subsystem (e.g., cell imagingsubsystem 112) that collects a plurality of images. The image data maybe label-free, meaning there is no staining of the cell culturesinvolved when obtaining the image data. The image data may includemultiple imaging modalities, as well as time-series image data.

In block 6506, the cell culture system may generate a plurality ofvisual categories from the image data. The cell culture system mayutilize an unsupervised learning engine within a computing subsystem(e.g., computing subsystem 110) to generate the plurality of visualcategories, as disclosed with respect to FIGS. 59-63 . For example, theunsupervised learning engine may divide the image data into a pluralityof image patches, reduce the image patch data into a lower dimensionalencoding space, and then identify repeating visual patterns in thereduced data set that may be classified into visual categories.

In block 6508, the cell culture system may associate the plurality ofvisual categories with a plurality of attribute categories. The cellculture system may also collect additional data such as assay profilesand labeled image data and utilize this information to associate avisual category with one or more attribute categories. The associationmay be aided by human intervention in which a person may review thevisual patterns and other collected information for a particular visualcategory, and then determine the attributes that the visual category isindicative of.

In block 6510, the cell culture system may label the image data with theplurality of attribute categories, producing annotated attribute maps ofthe one or more cell cultures. This information may be used by the cellculture system to make decisions about cell editing, cell culturegrowth, further testing, or other actions. In this manner, the method6500 provides an automated method of training the cell culture system toidentify visual patterns in observed cell cultures and associate themwith attributes that indicate information about cell quality, growthprogress, and other factors relevant to producing a desired output cellproduct.

FIG. 66 is a flow chart of a method 6600 of growing cells in a cellculture system in accordance with various implementations. The method6600 may be performed by one or more components in a cell culture system(e.g., cell culture system 100), such as an automated classificationsystem as disclosed with reference to FIGS. 59-63 . The method 6600 maybe performed during the manufacturing phase after the automatedclassification system has completed learning/training as described withreference to FIGS. 59-63 and 65 .

In block 6602, the cell culture system grows one or more cell cultures.The cell cultures may be grown in cell culture containers (e.g., cellculture containers 104) and be of the same cell type. The cell culturecontainers may allow for label-free imaging and editing in a closedsystem (e.g., a closed cassette). In block 6604, the cell culture systemmay obtain image data of the one or more cell cultures. The image datamay be collected by a cell imaging subsystem (e.g., cell imagingsubsystem 112) that collects a plurality of images. The image data maybe label-free, meaning there is no staining of the cell culturesinvolved when obtaining the image data. The image data may includemultiple imaging modalities, as well as time-series image data.

In block 6606, the cell culture system may generate one or moreattribute maps from the image data, in which each attribute mapcomprises an image of a cell culture annotated with cell attributes. Anunsupervised inference engine may take as input the image data and storemodel parameters such as visual categories and associated attributecategories. The visual categories and attribute categories may begenerated by an unsupervised learning engine within a computingsubsystem (e.g., computing subsystem 110) as disclosed with respect toFIGS. 59-63 and 65 . The unsupervised inference engine may be configuredto identify visual patterns in the image data corresponding to thevisual categories and label them with the appropriate attribute.

In block 6608, the cell culture system may determine one or more actionsbased on the one or more attribute maps. The actions may include, forexample, editing select cells in the one or more cell cultures,collecting assays on select cells in the one or more cell cultures, orchanging parameters of cell growth of the one or more cell cultures. Inthis manner, the method 6600 provides automated attribute classificationof cells during cell culture manufacturing, which may be useful inguiding and optimizing the manufacturing process, particularly in anautomated cell culture system.

Closed Cassette Systems

There is currently no bioreactor or other system in the art forclinical-grade manufacturing of cells that (1) allows 100% non-contactmeasurement of cells in culture to monitor and control thebiomanufacturing process, and (2) is sealed in a manner that allowsparallel manufacture in a non-sterile facility, and further, in somecases, allows editing of cell cultures based on image-derivedcharacteristics (e.g., in a cell culture system).

Such a system would enable a wide range of cell biomanufacturingprocesses at a scale, consistency, yield, and cost that are notcurrently achievable. This capability is particularly important totranslate emerging patient-specific therapies from the laboratory toclinical trials and ultimately to larger patient populations.

The systems and methods disclosed herein include a cell culturecontainer that includes a closed media path and at least one culturechamber suitable for aseptic cell manufacturing in a non-sterilefacility. The at least one cell culture chamber has at least one growthsurface for cells that is optically accessible for label-free imaging bytransmission and/or reflection illumination. The cell culture chambermay be liquid-filled and substantially free of any gas layer, and thegrowth surface may be is inverted for at least part of the cell cultureprocess in order to gravitationally separate debris and/or non-adherentcells from the culture surface. The cell culture container may provide asterile-sealed closed loop liquid system to support cell cultures grownin the cell culture container.

In some implementations, the cell culture container may include amechanism for selectively removing cells from the cell culture surfacewithout opening the media path, with the removed cells or cell fragmentsseparated at least in part by using the inverted configuration. In someimplementations, time-series imaging of the cells on the cell culturesurface and image processing of the resulting images may be used topredict the outcome of a cell culture process. This prediction may beused to manage the manufacturing process by discarding the cell cultureswith poor predictions, and/or starting back-up cultures, selectivelyremove cells within the cell culture chamber in order to improve thepredicted outcome, and manage the media inside the closed system, forexample the addition of fresh media, in order to improve or maintain thepredicted outcome. In some implementations, the cell culture containermay include a mechanism for agitating liquid in the cell culture chamberwithout opening the media path in order to dislodge debris or cells fromthe growth surface.

The various implementations disclosed herein may be used for scaling out2D cell culture processes in a manner compatible with good manufacturingpractice (GMP) requirements for cells and tissue to be used in patients.Furthermore, the disclosed implementations allow long-term processes tobe run, observed, and controlled in a sealed system, in order to allowdozens or hundreds of patient samples to be processed in parallel in asingle facility, without the risk of cross-contamination. The disclosedimplementations may be used for reprogramming of somatic cells intoinduced pluripotent stem cells (iPSCs), for differentiation of stemcells into cells and/or tissue for screening or transplantation, forexpansion of cells, for gene modification of cells, and otherapplications requiring multi-day processes where cells are maintainedwith nutrients, factors, vectors to be delivered, etc.

FIG. 67 is a diagram of a closed cassette system 6700 for use in a cellculture system in accordance with various implementations. The closedcassette system 6700 may be an implementation of the cell culturecontainer 106 shown in FIG. 1 . The closed cassette system 6700 mayinclude a cell culture chamber 6702 supporting the growth of an adherentcell culture 6704. In some implementations, the closed cassette system6700 may include more than one cell culture chamber 6702. A closedliquid loop 6706 provides the cell culture chamber 6702 with fluid mediaand allows for media and reagent exchange. The closed liquid loop 6706may be an aseptically-sealed liquid system (also referred to as afluidic system), built for example using planar microfluidic channelsand/or sterile tubing that may be sterile-welded and pre-sterilizedusing gamma and/or UV radiation. The closed liquid loop 6706 enables thegrowth and maintenance of the cell culture 6704 over an extended periodof time for the purpose of reprogramming, differentiating, gene-editingand/or expanding the cells.

The closed liquid loop 6706 may include a plurality of reservoirs,typically sterile bags that may deflate or inflate over the course ofthe cell culture process. The reservoirs may include a fresh mediareservoir 6708 which supplies cell culture nutrients, vitamins, andother factors, and a waste reservoir 6710 into which spent media ispumped during complete or partial media exchanges. Additional reagentsor buffers (for example for pH control) are shown as reservoirs 6716.There may also be a debris collection reservoir 6712 and cell collectionreservoir 6714. Debris and/or cells are cleared from the cell culturechamber 6702 and moved to the debris collection reservoir 6712 to removethem from the media loop through the use of a filtration feature 6728.Debris are typically discarded, while the cells captured in the cellcollection reservoir 6714 are the output cell product (e.g., output cellproduct 118 in FIG. 1 ) of the cell culture process.

A pump 6718 circulates liquid through the closed liquid loop 6706. Thepump 6712 shown in FIG. 67 is a peristaltic-type pump, but in generalthe closed cassette system 6700 may use other configurations compatiblewith a closed system. In the case of a peristaltic pump, it may act upontubing or a channel in a planar microfluidic system. The pump 6718 mayrun forwards as well in reverse. Reverse pumping may be used to clearthe cell filtration unit and pump the filtered solids (debris and/orcells) into the debris collection reservoir 6712 or cell collectionreservoir 6714. The closed liquid loop 6706 may additionally be pumpedin reverse to ensure even distribution of media within the cell culturechamber 6702. The pump 6718, in conjunction with actuated valves 6724(only some of which may be shown in FIG. 67 ), controls all the liquidprotocols on the closed cassette system 6700.

The closed cassette system 6700 may also include a mixing and exchangesection 6720, which is shown schematically in FIG. 67 . The mixing andexchange section 6720 may perform two functions. First, it serves topromote mixing in the circulated liquid to ensure homogeneity once itreaches the cell culture chamber 6702. For example, if a small amount offresh media has been added, the mixing and exchange section 6720 servesto mix it with the existing media. The mixing and exchange section 6720may have a liquid feedback mechanism to provide a greater mixing factor.

A second function of the mixing and exchange section 6720 may be gasexchange. For example, the dissolved oxygen level in the fluid media maybe an important factor in certain bioprocess. When outfitted with gasexchange surfaces/mechanisms, the mixing and exchange section 6720 maybe used to control the dissolved oxygen and other gas concentrations inthe circulated media. In cases in which pH is controlled indirectly(rather than by addition of liquid), the mixing and exchange section6720 may be used to control dissolved CO₂. In cases in which cavitationmechanisms (e.g., laser, ultrasound, or other) are used to edit cellcultures 6704 within the cell culture chamber 6702, the mixing andexchange section 6720 may be used to control overall dissolved gasconcentration, potentially with an inert gas that has no other effect oncell culture, for the purpose of maintaining a stable threshold andpredictable energy transfer for cavitation.

Temperature may be separately controlled for the mixing and exchangesection 6720, or even within different parts of the mixing and exchangesection 6720, to control gas solubility for the purpose of facilitatinggas exchange. Additionally, external gas pressure may be controlled inone or more parts to facilitate gas exchange. For example, in a firstportion of the mixing and exchange section 6720 the media temperaturemay be raised and external gas pressure is at below atmosphericpressure, in order to maximize outgassing (for example, to remove CO₂,which is a product of the live cell culture). In a second section of themixing and exchange section 6720 temperature is lowered and external gaspressure is at above atmospheric pressure to maximize transfer of O₂ orother gases into dissolved form in the liquid media to support cellculture. One or more bubble-trapping and removal stages (not shown) maybe integrated into the closed liquid loop 6706 to trap and remove, via agas-permeable membrane and reduced external gas pressure, any gas thatcomes out of solution so it does not interfere with the cell culture orliquid loop functions.

The closed cassette system 6700 may also include a sensing section 6722,which is shown schematically in FIG. 67 . The sensing section 6722 maybe used to monitor media conditions in a non-invasive manner. In theexample shown in FIG. 67 , the sensing section 6722 includes twocolorimetric patches (top and bottom circles) inside the closed liquidloop 6706. The optical characteristics of the patches may vary with pHand dissolved oxygen, respectively, and may be read using an externallight source and detector. Other media property and components may bemonitored with similar patches.

In the center of the sensing section 6722, a circular outline is shownthat represents a clear optical path for transmission, reflection, orscattering measurements performed without the aid of inserted materials.For example, spectroscopic transmission measurements in the ultraviolet(UV), visible, near infrared (NIR), mid-wave infrared (MWIR) orlong-wave infrared (LWIR) may be performed to assess media contents,including but not limited to nutrients, waste products, vitamins, andbioprocess byproducts. Alternatively, Raman spectroscopic measurementmay be made of the media and its contents. In addition, scatteringmeasurements at one or more wavelengths and scattering angles may bemade to assess media contents. The measurements made in the sensingsection 6722 may be used in a closed-loop control of the closed cassettesystem 6700. For example, data from the sensing section 6722 may be usedto make decisions about adding fresh media, adding liquid to control pH,or changing gas exchange rates or composition. In addition, thesemeasurements, in conjunction with imaging-based measurements, may beused to track the cell culture bioprocess and predict outcomes usingstatistical models (or to train these statistical models, based onendpoint results).

The closed cassette system 6700 may also include a plurality of ports6726, positioned at various points along the closed liquid loop 6706.These may be single-use ports (e.g., for filling or inoculating the cellculture chamber 6702 or entire closed cassette system 6700, or forharvesting output cell product) that are sterile welded after use. Suchports may also be fitted with one-time sterile connectors.

In typical usage of the closed cassette system 6700, incrementalexchange of media is performed over time, either on a fixed timeschedule, or more preferably based on some combination of time andobserved cell culture characteristics (total cell count, etc.). Mediaexchange may be monitored by a computing subsystem (e.g., computingsubsystem 110) of a cell culture system that utilizes the closedcassette system 6700. Such incremental exchange may be performed byclosing the valve in the flow loop situated between the waste outlet(e.g., outlet leading to the waste reservoir 6710) and fresh media inlet(e.g., inlet from the fresh media reservoir 6708), opening the wasteinlet, opening the fresh media inlet, and then activating the pump 6718in the forward direction for a given duration. In this manner, anyamount from a small fraction up to the entirety of the media in theclosed cassette system 6700 may be replaced, depending on the pumpingduration and speed. The closed cassette system 6700 may include othercomponents not shown in FIG. 67 , such as additional pumps, valves,reservoirs, and sensors.

In some implementations, the closed cassette system 6700 comprisesmultiple one-time connector ports for fresh media replenishment duringlonger processes. In some implementations, the media composition isconstant over time. In some implementations, the media compositionchanges over the processing time. In some implementations, the mediacomposition changes based on a reprogramming phase, a differentiationprocess, or both. In addition, add multiple one-time disconnect portsfor waste media, to remove waste media and debris over time. Both ofthese allow a compact cassette format that nevertheless enableslong-term processes or processes that have high media requirements.

In some implementations, dissolved oxygen in the fluidic system of thecassette is controlled depending based on a reprogramming process or adifferentiation process. For example, hypoxic conditions can often makeiPSC reprogramming more efficient.

In some implementations, for the closed liquid loop 6706, the processmodule monitors dissolved oxygen via an optically-interrogated sensorpatch, and oxygen levels are dynamically adjusted based on the measureddata. The process module may comprise connectors for two or more gaslines (e.g., oxygen connector, nitrogen connector, oxygen/nitrogenconnector). In some implementations, the process module comprises anon-board valve for mixing gases in specific concentrations. The mixedgasses can flow via a pluggable connector or an open port that betweenthe cassette 6700 and the process module to a gas exchange section. Inone example, a surface of the growth chamber is gas-permeable, whereinthe atmosphere surrounding the growth chamber(s) is directly controlledby the process module.

In some implementations, the connector is a one-time aseptic connection(e.g., for a non-ultraclean/sterilized environment). In someimplementations, the one-time connector allows tubes to be connectedaseptically using removal membranes (e.g., Sartorius Opta SFT AsepticTube Connectors). In some implementations, a plurality tubes areconnected to form one-time connector formed by aseptic tube welding by awelding tool (e.g., by a Terumo TSCD-II Sterile Tubing Welder). In someimplementations, at least a portion of the plurality of tubes comprise athermoplastic elastomer (TPE), such as PVC, where tubes, includingliquid-containing tubes. In some implementations, the one-time asepticconnection comprises a one-time crimped disconnector inserted intotubing with a tubing insert, and crimped by a crimping tool (e.g.,Sartorius Quickseal Disconnectors).

In addition, non-aseptic connectors, such as Luer lock connectors, maybe used to connect or disconnect media, waste, reagent or other bagsfrom the cassette in a well-sterilized flow hood environment.

FIG. 68A is a diagram of a cell culture chamber 6800 in a closedcassette system in accordance with various implementations. The cellculture chamber 6800 may be similar to cell culture chamber 6702 in FIG.67 . FIG. 68A shows both a top view and a cross-section view of the cellculture chamber 6800. The cell culture chamber 6800 includes at leastone inlet channel 6802 that is used to deliver media into the cellculture chamber 6800. This media may come from a closed liquid loop ofthe closed cassette system. The media may include fresh media and/orreagents are incrementally added and mixed into the fluid flow of theclosed liquid loop. The fluid flow, which is typically slow and laminar,is expanded gradually through an expansion section 6804 into the cellculture chamber 6800. Additional features may be added to make theoverall flow profile uniform.

The target is to establish a uniform, very low velocity flow in thetarget cell growth region 6808. In many cases, the goal is to minimizecontinuous and/or directional shear stress on the cells in culture,preferably keeping it to <5 dyne/cm², and preferably <1 dyne/cm². Insome implementations, the shear stress exerted on the cells in cultureis less than about 10 dyne/cm², 9 dyne/cm², 8 dyne/cm², 7 dyne/cm², 6dyne/cm², 5 dyne/cm², 4 dyne/cm², 3 dyne/cm², 2 dyne/cm², or 1 dyne/cm².Media is removed from the cell culture chamber 6800 via outlet channel6810. It should be noted that for portions of the cell culture process,the flow direction may be reversed (i.e., media enters from the outletchannel 6810 and exits from the inlet channel 6802).

Cells 6806 are cultured within the cell culture chamber 6800,potentially confined via surface treatment and/or an editing system totarget cell growth region 6808. Within this region, the cells areobservable via a label-free imaging system (e.g., cell imaging subsystem112). The imaging may operate in one or more known modalities, includingbut not limited to transmission imaging, reflection imaging,brightfield, darkfield, phase, differential interference contrast (DIC),quantitative phase imaging (QPI), Fourier ptychographic imaging intransmission or reflection, holographic imaging, or combinations ofthese. All the cells 6806 may be imaged over time to monitor theprogression of the cell culture and make predictions with respect toquality and yield. For this purpose, registration marks 6812 visible tothe cell imaging subsystem may be provided to provide stable spatialreferences over time and accurately monitor cell behavior at a colony oreven cell level.

The cells 6806 may be an adherent cell culture adhered to the topsurface of the cell culture chamber 6800, as shown in the cross-sectionview of FIG. 68A. The cells 6806 may initially be cultured on the bottomsurface of the cell culture chamber 6800 until they adhere to thesurface, and then the cell culture chamber 6800 may be inverted so thatthe cells 6806 reside on the now-top surface as shown in thecross-section view. Inversion, enabled by a growth chamber that iscompletely filled with media, may be utilized to separate non-adherentcells, cell debris, and other debris or particles of density greaterthan the cell media from the adherent cell culture. For example, whenreprogramming suspension somatic cells into iPSCs (which are adherent),inversion of the cell culture chamber 6800 may gently separate somaticcells that are not successfully reprogrammed from the reprogrammed iPSCsusing gravity. The somatic cells that fall to the bottom surface maythen be washed out of the cell culture chamber 6800. In the reversecase, in which stem cells are differentiated into suspension cells,successfully differentiated cells may be gently separated by invertingthe cell culture chamber 6800.

In another example, the cell culture chamber 6800 may be used to growadherent cells that are genetically reprogrammed or have episomalvectors delivered to them for non-integrating expression, in which theprogramming includes an antibiotic resistance. The antibiotic maysubsequently be used to kill the undelivered cells. The debris fromthese cells may then fall away from the top growth surface of the cellculture chamber rather than potentially contaminating the remainingsuccessfully delivered (hence antibiotic-resistant) cells. In anotherexample, an editing mechanism (e.g., a laser) may be used to lyse ordamage specific cells on the growth surface by means of mechanicalforce, heat, ultrasound, electrical fields or photodamage in a mannercompatible with a closed cassette, and the damaged/destroyed cell debrisis gravitationally separated from the untouched live cells, such that itdoes not settle on the live cells. In another example, a matrix orcoating is used under the cells that may be selectively altered/removedto release the attached cells. This alteration being performed in amanner that is compatible with a closed container. The separationmechanisms described herein may be used to remove unwanted cells, or toremove wanted (product) cells, or to remove select cells for analysis.

As an illustrative and non-limiting example, a prototype adherent cellgrowth chamber as shown in FIG. 68A supports over 50 cm² of cell culturearea on a single surface, and has liquid filled height of approximately0.5 mm, with a total volume of approximately 3 ml for very highefficiency cell culture. This prototype chamber can be modified forhighest-uniformity liquid flow (elimination of angled corners inparticular). The chamber in this particular example includes two piecesof 110×74 mm 0.17 mm thick borosilicate glass coverslips, one with twoliquid ports cut through it, separated by an 0.5 mm thick siliconegasket with adhesive surfaces that has been cut to define the chamber.Tubing connectors are attached to the liquid ports. FIG. 68B is an imageof an exemplary cell culture chamber. This chamber supports over 50 cm²of cell culture area on a single surface, and has liquid filled heightof approximately 0.5 mm, with a total volume of approximately 3 ml forvery high efficiency cell culture. This chamber has not yet beenmodified for highest-uniformity liquid flow (elimination of angledcorners in particular). The chamber consists of two pieces of 110 mm×74mm 0.17 mm thick borosilicate glass coverslips, one with two liquidports cut through it, separated by an 0.5 mm thick silicone gasket withadhesive surfaces that has been cut to define the chamber. Tubingconnectors are attached to the liquid ports. FIG. 68C shows an exemplaryhiPSCs grown under continuous media flow in a liquid-filled chamber witha height of less than about 1 mm height.

FIG. 69 is a diagram illustrating removal of cells from a cell culturechamber 6900 in a closed cassette system in accordance with variousimplementations. The cell culture chamber 6900 may be similar to cellculture chamber 6702 in FIG. 67 . Cell colonies 6902 or individual cells6904 may be selectively lysed via a steered pulsed. For example, in aniPSC reprogramming process colonies may be kept separated to ensureclonality. A cell imaging subsystem (e.g., cell imaging subsystem 112)may collect images of the cell culture chamber 6900 and a computingsubsystem (e.g., computing subsystem 110) may utilize various machinelearning processes to determine whether one or more of the cell colonies6902 may be in danger of merging. The computing subsystem may thencontrol a cell editing subsystem (e.g., cell editing subsystem 112) toremove at least one of the cell colonies 6902. Additionally, individualcells or groups of cells may be determined by a human viewer or acomputer algorithm to be spontaneously differentiating, in which casethey may be removed via the cell editing subsystem as shown herein.

FIG. 70 is a diagram illustrating agitation of cells from a cell culturechamber 7000 in a closed cassette system in accordance with variousimplementations. The cell culture chamber 7000 may be similar to cellculture chamber 6702 in FIG. 67 . FIG. 70 shows both a top view and across-section view of the cell culture chamber 7000. The systems andmethods disclosed herein may allow for agitating or mixing of liquidwithin the cell culture chamber 7000 without opening the closed cassettesystem. In this case, the agitation mechanism may be used to detach celldebris from the culture growth surface so that the debris then settleson the opposite surface of the cell culture chamber 7000 (e.g., thebottom surface). The turbulent mixing effect of the mechanism isindicated in the top view and cross-section view by arrows 7002.

The agitation mechanism may include a number of physical modes,including but not limited to: magnetic mixing in which one or moremagnets are resident inside the cell culture chamber 7000, and anexternal magnetic actuator is used to translate and/or rotate thesemagnets to achieve local mixing and agitation; mechanical actuatorsacting on the upper and/or lower surfaces of the cell culture chamber,potentially in conjunction with liquid flows or stoppage; laser-basedtechniques where a pulsed laser is used to induce cavitation inside thecell culture chamber 7000 in order to produce local mechanical forcesand mixing (the focus of this laser may be on the surface opposite thecell culture, for example); or ultrasound transmission into the cellculture chamber 7000 that may be uniformly distributed or focused onspecific regions where debris needs to be dislodged. As a result of theagitation, the detached cells and/or cell debris 7004 settles on thelower surface. From there the cell debris 7004 may be removed by one ormore mechanisms including the above, but also liquid flow andgravitational techniques (e.g., tilting).

FIG. 71 is a diagram of a single-use portion 7100 of a closed cassettesystem for use in a cell culture system in accordance with variousimplementations. The single-use portion 7100 may be configured tosupport a single cell culture process before being discarded. Thesingle-use portion 7100 may include a chamber, fluidics, and supply andwaste bags and associated tubing, similar to those shown in FIG. 67 .All of the components of the single-use portion 7100 may be sterilized,filled under aseptic conditions, and then used in a cell cultureprocess. After use, the bags containing the output cell product areremoved using a sterile weld, and the remainder of the single-useportion 7100 may be disposed of properly.

The single-use portion 7100 may include a body 7102 housing fluidicsystem 7108 as well as cell culture chamber 7106. The body 7102 may betransparent or semi-transparent to allow for visual or automated imagingof the fluidic components and channels, for example to verify that thereis no contamination, blockage, bubbles, etc. Bags 7104 are attached tothe single-use portion 7100. The bags 7104 may contain media reagents aswell as waste products and cellular products. The fluidic system 7108 inthe single-use portion 7100 may include channels for circulating liquid,valve sections, pump sections, gas concentration control fluidics,non-invasive sensing patches, etc.

FIG. 72 is a diagram of a permanent portion 7200 of a closed cassettesystem for use in a cell culture system in accordance with variousimplementations. The permanent portion 7200 may include a reusablehousing 7202 that encloses the single-use portion of the closed cassettesystem (e.g., single-use portion 7100). The combination of the permanentand single-use portions may form a complete closed cassette system(e.g., closed cassette system 6700). The permanent portion 7200 may alsoinclude at least one clear window 7204 to allow complete imaging of thecell culture chamber located in the single-use portion. In someimplementations, the window 7204 may be on both sides of the cellculture chamber in order to allow transmission imaging. In otherimplementations, the window 7204 may only be located on one side of thecell culture chamber when reflective imaging is sufficient (i.e., lightsource and sensor on same side of chamber).

A compartment 7206 houses the supply, waste and product bags of thesingle-use portion and may provide one or more temperature-controlledchambers for long-term storage (for example, cellular products may beheld at 37° C., while some reagents are held at 4° C. until use). Insome implementations, the permanent portion 7200 may also includeactuators for actuating valves and pumps on the single-use portion ofthe closed cassette system. For example, spring-loaded solenoids mayapply pressure to the tubing on the disposable fluidics to keep valvesclosed in their unactuated state, and when an electrical current isprovided, the solenoid opens the valve by releasing pressure. Similarly,pumps may be driven by electromechanical systems within the permanentportion, for example by driving a series of cylindrical rollers in asemicircle along the path of tubing on the single-use portion toinitiate peristaltic pumping.

A mechanical rail 7210 may integrated in the permanent portion 7200 toprovide alignment within one or more pieces of equipment. For example,the closed cassette system may reside in equipment that also includesimaging systems, power systems, central computing systems, heating andcooling systems, cassette movement systems, and other components tosupport parallel cell culture processing on multiple closed cassettesystems. In one implementation, such equipment may include a serverrack, and the mechanical rail 7210 may allow the closed cassette systemto slide in and out of the server rack. The permanent portion 7200 mayalso include pluggable connectors 7208 that interface with connectors onthe equipment (e.g., server rack). The pluggable connectors 7208 mayinclude, but are not limited to, electrical connectors to power on-boardelectronics and actuators, data connectors to collect sensor and statusinformation centrally, liquid connectors for circulating liquid fortemperature control, and gas connectors to supply gas for maintaininggas concentrations in the cell culture media.

FIG. 73 illustrates various cell culture chamber configurations in aclosed cassette system for use in a cell culture system in accordancewith various implementations. These configurations may include a singlelarge chamber configuration 7302, a multiple small chamber configuration7304, a small and large chamber configuration 7306, and otherconfigurations not shown in FIG. 73 but known to persons of skill in theart. The single large chamber configuration 7302 may be used for cellexpansion, for example. The multiple small chamber configuration 7304may be used in cases in which multiple clonal populations are desired inorder to have a diversity of product, for example. The small and largechamber configuration 7306 may be used to first prime cells in a smallchamber using relatively little reagent (this may include delivery ofcompounds into the cells), followed by reprogramming or differentiationand expansion in the larger chamber. In all of these configurations, itis possible using appropriate valving and/or filtration to keep cellsfrom inadvertently moving from one chamber to another. However, as inthe last example, the fluidics may be configured to explicitly allowmovement from one chamber to another through valving filtration andpumping operations.

Modular Bioprocessing System

Bioprocessing is the process of using living cells or their componentsto obtain a desired output. Current bioprocessing equipment is availablelargely in two types. The first type are large-scale bioreactors derivedoriginally from the chemical industry and repurposed for cell-basedprocesses such as protein or viral production. These bioreactorstypically using large steel tanks, but more recently have been fittedwith one-time-use bags or scaled down to glass-based stirredbioreactors. These systems are usually surrounded with bespoke, sealedtubing and other modifications to make the bioreactors suitable forhandling biological materials. The second type of bioprocessingequipment are small-scale systems derived from manual R&D laboratoryinstruments, typically including benchtop instrumentation and utilizingmicrowell plates or small flasks. In some cases, small scale systemshave been scaled up to larger containers, and custom systems have beendeveloped in order to transport, fill, and handle stacks of plasticcontainers containing cell cultures.

In the case of large scale bioreactor systems, the amount of datacollected during the bioprocess is often minimal. There has been alargely stalled push to get more measurement and control in tankbioreactor-style systems. However, the proposed measurements, even ifimplemented, would be minimal representations of the state of thebioreaction, typically measurements of nutrients, waste products, cellmass/density, pH, O2, temperature, and a few other factors that allowfor better control of the process. Some additional sampling-basedmeasurements allow for more detailed, but less frequent, measurement ofthe cell mixture. However, the physical volumes of these systems arelarge, and the data volume is quite low.

Recent autologous cell and gene therapy processes, such as CAR-Ttherapies, have taken a similar approach, simply miniaturized. It hasbecome increasingly clear that the absence of higher-bandwidthmeasurement, monitoring, and feedback control are a challenge in thesetherapies, where patient-to-patient variations can lead to poorconsistency and yield. On-time delivery of therapies is crucial, andthese drawbacks may lead to significant delays. Some bioprocessingequipment suppliers have sought to build automated, modular units toaddress these issues, but although these provide the ability to performcell processes in non-sterile facilities, they still keep to theconvention of separating biological equipment from the datainfrastructure, and are built with only human operators in mind.

On the other hand, in the small scale system model, derived from R&Dlaboratory equipment, there is at least the potential to gather moredata on the actual cell culture conditions by use of imaging, becausemany formats were developed specifically to allow microscopy and otheroptical measurements. However, imaging measurements of cell culture aredone almost only as “spot checks” rather than to quantitatively assessthe cells or guide process parameters. High content imaging has largelyremained in the domain of R&D or is used in quality control assays atthe end of a cell culture process. For example,immunofluorescent-labelled imaging may be used on a small sample thatseeks to reflect the whole product.

Bioprocessing systems should ideally collect detailed, fine-grainedinformation about the progression of the process, the state of cells andcell colonies, and potential problems with purity or yield far inadvance of final quality control assays. This fine-grained data,together with appropriate control algorithms, may be used to control andoptimize both process parameters (such as nutrient flow, productharvest, vitamin or gas concentrations, temperature, pH, etc.) and toactively guide the cell cultures by use of selecting cell removal orediting based on imaging results. In addition, other optical techniquessuch as spectroscopy may be employed in such formats to extract datarelated to biochemical constituents within the cell media or cell mass.

With such expanded use of online imaging and spectroscopic techniques,the amount of data generated per biological sample in process explodes.Take for example the equivalent of a T-225 flask (225 cm² growth area)used in a process for differentiating cells from induced pluripotentstem cells (iPSCs). Using brightfield imaging with a 5-layer Z stack, ata cycle time matching the rough cell division (18 h), a resolution of 1micron, and a standard 16 bits per pixel, the daily raw data stream ofimaging alone is 150 Gigabytes. This imaging data must be collected,processed, interpreted, and made into actionable information relevant tobioprocess prediction and control. Scale up to a facility in whichhundreds of patient samples are processed in parallel, and the scale andreach of the data infrastructure alongside the bioprocessinginfrastructure becomes clear: many terabytes per day flow through thebiomanufacturing environment. Small scale data storage means are nolonger useful. An infrastructure in which biology and data coexist andwork together is required.

Another issue in bioprocessing is the ability to automate processesefficiently. The current approach includes setting instruments onbenches (similarly to how they would be situated in a manual R&Dlaboratory), placing one or more robots between the instruments, andthen training the robots to very precisely find the correct locations toplace or pick consumables to/from the various instruments. Any movement(swap-out for repair, etc.) of an instrument requires retraining. Almostevery instrument has a slightly different mechanical interface, usuallydesigned primarily with manual R&D lab operations in mind, withmechanical interfaces to robotic systems as an afterthought. As aresult, building an automated system with even just a few instrumentsbecomes a major undertaking for which specialized contractors are hired,custom benches are fabricated, and the reach of a central robot arm mustbe carefully calculated. Once built, the setup offers limitedexpandability. As a result, the up-front investment in time, dollars,and real estate footprint for incremental capacity can be verysignificant.

Some companies have attempted to remedy the expandability issues withlarge-scale transport system for microplates and extensive customautomation hardware. Others have built more linear robotics that movealong shelving constructed specifically for each piece of equipment,with appropriate widths, heights, etc. for shelves. However, thesesystems rely on specific positioning of instrumentation to properlyinterface with the robotics, and where the robotics are required to behighly flexible, with multiple degrees of freedom, and therefore quiteexpensive.

Additionally, because of the format of these systems and the constraintsof the type of robotics and automation that is required the systems endup having a large, planar footprint. The result resembles a warehousewhere bulk goods of various shapes and sizes are simply placed onshelving of varying proportions. When faced with these analogous issues,large warehouse operators have tried to standardize shelving andstorage, and then try to automate the storage and retrieval process andadopt a vertical format for space and transport logistical efficiency.Similarly, in order to scale up biology, and in particular bioprocessingand biomanufacturing, a more modular, standardized, expandable, anddata-integrated system that minimizes footprint and transport complexityis needed.

The systems and methods disclosed herein utilizes industry standard dataand communications infrastructure and equipment to serve as the basisand backbone for a highly modular bioprocessing system. Thebioprocessing modules used in these systems may be closed cassettes thatare fully imagable for monitoring and control purposes, including theability to actively edit cell cultures by removing cells or cellcolonies during the course of the process. The present implementationsmay utilize such cassette-based systems, but may also utilize existingmicrowell plate, flask, and larger (closed) container formats.

The bioprocessing modules may be sized to fit within standard serverrack units, with heights measured in standardized units of U (1U, 2U,4U, etc.) and widths the same as computing, storage, and communicationsequipment. The modular bioprocessing system also includes common modulesthat may be shared between multiple bioprocessing modules on the samerack, such as data storage modules, computing modules, power supplies,communications modules, environmental control modules, laser modules,liquid handler modules, and imaging modules. This not only allows for ahighly modular, incrementally expandable format for bioprocessingfacilities, but also allows for very tight integration betweenbioinstrumentation and data processing to address the high volumes ofdata and communication in fully-monitored, closed-loop bioprocessing.Other advantages of such a system include fast setup and delivery,easier automation, incremental expansion, use of existing modular unitsfor power, environmental management, and direct integration with datainfrastructure and modules.

The modular bioprocessing systems may have standardized dimensions, suchas 19 inch width enclosures, various depths including but not limited to24″, 36″ and 48″, and various heights up to the industry-standard 42U(in which 1U=1.75″). All instrumentation and equipment in the variousimplementations may mount into these racks and have heights in 1Uincrements, so positioning may be calculated purely from rack positionindex. The front-facing panel of the instrumentation modules may have aloading area to load/unload the micro plate, flask, cell culture vessel,or cell culture cassette for which the system is designed. The modularbioprocessing system may also include vertical transport mechanisms tomove cell culture containers (e.g., microwell plates) in and out ofbioprocessing modules and onto/off of horizontal transport mechanismsdesigned to move cell culture containers between modular bioprocessingsystems and other locations. These mechanisms may be automated in orderto form a fully automated bioprocessing facility, but may also allow foreasy human interaction with the system.

The systems and methods disclosed herein include a modular bioprocessingsystem that includes a rack, one or more bioprocessing modulesconfigured to fit within the rack, the one or more bioprocessing modulesconfigured to accept one or more cell culture containers, and aplurality of common modules configured to fit within the rack, theplurality of common modules shared by the one or more bioprocessingmodules. This system has many advantages over current bioprocessingdesigns, which may include, but are not limited to, easy setup,alteration, and expansion in capacity, and easy integration with data,communication, and power systems.

FIG. 74 illustrates a modular bioprocessing system 7400 in accordancewith various implementations. The modular bioprocessing system may be animplementation of a cell culture system (e.g., cell culture system 100),or may be part of a larger cell culture system that includes one or moremodular bioprocessing systems. The modular bioprocessing system 7400 mayinclude a rack 7402 for holding all the modular elements in the modularbioprocessing system 7400, including both data processing andcommunications modules, as well as bioprocessing modules. The rack 7402may have standardized server rack sizes. For example, server rack heightmay be measured in units of U (1U=1.75 inches). For example, a rack witha size of 42U has a usable height of 73.5 inches. The rack 7402 may alsohave standard depth and width dimensions. This allows for a number ofstandard-shaped modular elements to be placed in the rack 7402, ratherthan requiring custom-sized components.

The modular bioprocessing system 7400 may also include one or morecontainer interfaces 7404 for accepting and holding cell culturecontainers. These cell culture containers may include, but are notlimited to, standard microwell plates (for example 6-, 12-, 24-, 48-,96-, 384- . . . well plates), cell culture flasks, microfluidicchambers, or custom cassettes for cell cultures. In FIG. 74 , animplementation that uses standard microwell plates is shown. In thiscase, the container interface 7404 include a plate holder that extendsfrom the front of each bioprocessing module for loading/unloadingmicrowell plates. The microwell plates are then retracted into eachbioprocessing module for processing or storage.

The modular bioprocessing system 7400 may also include one or morebioprocessing modules 7406. Each bioprocessing module 7406 may be aclosed container (i.e., the internal components are not exposed toexternal components that may contaminate the container) that includes acell culture container holding a biological sample to be processed(e.g., differentiated cells that are processed into iPSCs or vice versa)and components that support the growth, editing, cleaning, imaging,sensing, and other functions for processing the biological samples. Thebioprocessing modules 7406 may include, but are not limited to, closedcassettes that are fully imagable for monitoring and control purposes,microwell plates, flasks, and other closed container formats. Eachbioprocessing module 7406 may maintain independent environmentalconditions corresponding to different cell processes or cell processstages or states. For example, the temperature for each module may beset differently, pH may be controlled, or the dissolved oxygen level maybe set differently in each module in order to maintain a hypoxicenvironment for some cell culture processes or stages of processes.

The modular bioprocessing system 7400 may also include one or moreliquid handler modules 7408 that is configured to change media in thebioprocessing modules 7406. Appropriate tubing and containers for mediaand waste may be connected to the rear (utility) side of the liquidhandler module 7408 and connected to the bioprocessing modules 7406. Asingle liquid handler module 7408 may support one or more bioprocessingmodules 7406. For example, bioprocessing modules 7406 that contain thesame biological samples undergoing the same process may share a liquidhandler module 7408. In other implementations, there may be a one-to-onecorrespondence between bioprocessing modules 7406 and liquid handlermodules 7408. The liquid handler modules 7408 may include relativelysimple media exchange modules, which withdraw waste media from cellculture containers, and refill with fresh media. Such media exchangefunctionality may further include centrifugation in the case ofsuspension cell cultures. Other modular liquid handling implementationsmay include the ability to add multiple reagents to wells withinmicroplates in various combinations, for the purpose of drug screeningor high-throughput cell process development. Other modular liquidhandling implementations may include the ability to simultaneously loadmultiple cell culture containers and affect transfers between thesecontainers, for example to distribute cell samples among multiple wellsfor subsequent quantitative polymerase chain reaction (qPCR analysis),which may also be implemented in the present application via a modularunit.

The modular bioprocessing system 7400 may also include one or moreimaging modules 7410 that are configured to capture time series imagesof biological samples cultured in the bioprocessing modules 7406.Different imaging modules 7410 may have different capabilities. Forexample, two label-free (brightfield, phase, quantitative phase,transmissive or reflective darkfield, etc.) modules may be used tocapture label-free time series images of cell cultures over days, and asingle fluorescent imaging module may be used to capture high-contentmulti-channel fluorescently-labelled cell culture images at an endpoint.In some implementations, one imaging module 7410 may be configured tocapture multiple types of images. The imaging modules 7410 may beconfigured to automatically capture images based on a schedule, theschedule set by a control module within the modular bioprocessing system7400 or by an external controller that controls multiple modularbioprocessing systems.

One of the advantages of the modular bioprocessing system 7400 is thatmodules may share resources, similar to how resources may be shared indata server rack configurations. For example, the modular bioprocessingsystem 7400 may include a power supply module 7412 provides power (forexample, 24V DC) to all modules in the system, with redundancy.Similarly, the modular bioprocessing system 7400 may also include anenvironmental control module 7414 that is configured to provide heatingand cooling capacity via liquid to all modules in the system. Forexample, the environmental control module 7414 may maintain cellcultures at 37° C., reagents to be maintained at 4° C., anddata/computing modules to be cooled to appropriate operatingtemperatures even under high loads. The modular bioprocessing system7400 may utilize standardized liquid connectors and distributionmanifolds used in cooling CPU/GPU server racks because of thestandardized setup of the rack 7402 and other modules.

The modular bioprocessing system 7400 may also include one or more datastorage modules 7416 and computing modules 7418. The data storagemodule(s) 7416 may be configured to store images collected by the one ormore imaging modules 7410, sensor data collected by various sensors inthe modular bioprocessing system 7400, and data and applications used bythe computing modules 7418. The computing module(s) 7418 may beconfigured to perform various data processing and analysis functionsrelated to bioprocessing the cell cultures in the bioprocessing modules7406. For example, the computing module(s) 7418 may perform imagepre-processing, registration, normalization, and stitching functions forthe imaging modules 7410, reducing or eliminating the need for dedicatedprocessors or computing modules for each imaging module 7410, andpotentially significantly distilling or compressing imaging data beforeit is transferred to a centralized location (either on-premises, inanother location including cloud resources, or both in a hybridarchitecture). The computing module(s) 7418 may also perform other dataprocessing, input/output, and communications functions for the modularbioprocessing system 7400.

The modular bioprocessing system 7400 may be communicatively connectedto a central controller, such as a central server that controls one ormore modular bioprocessing systems 7400. For example, there may bemultiple modular bioprocessing systems 7400 located in a room, and theremay be wired and/or wirelessly connected to a central server thatcontrols the operation of each modular bioprocessing system 7400. Thecentral server may also collect data from each modular bioprocessingsystem 7400, and may also provide a user interface for a person to viewdata (e.g., imaging data) collected from any modular bioprocessingsystem 7400, monitor the status of any bioprocessing module, and controlany of the modules in any modular bioprocessing system 7400. The centralserver may implement many functions, including scheduling automatedprocessing schedules of cell cultures, alerting users of emergencyconditions in any modular bioprocessing system 7400, and presentingreal-time operational data for any modular bioprocessing system 7400.

The modular bioprocessing system 7400 shown in FIG. 74 is a full-heightrack. However, it should be clear from the modular nature of the systemthat smaller systems are feasible. For example, a minimal system forcontinuous cell culture measurement may include one bioprocessing module7406, one liquid handler module 7408, one imaging module 7410, plusshared systems. The system may fit into a very compact rack suitable foreven the densest environments such as university laboratories. Themodular bioprocessing system 7400 may include other components notillustrated in FIG. 74 , and may include variations known to persons ofordinary skill in the art.

FIG. 75 illustrates container transportation functionality in a modularbioprocessing system 7500 in accordance with various implementations.Because of the modular nature and vertical format of the variousimplementations, a highly simplified cell culture container transportmechanism is possible. Moreover, the transport is compatible withside-by-side work with human operators, unlike robotic transport systemswhere a potentially hazardous robot arm sits in the center of a clusterof bioinstruments. The standardized modular format disclosed hereindramatically simplifies the requirements for such an automated transportsystem, since it defines discrete vertical rack locations for containerpickup/drop-off, and a fixed horizontal position, allowing asingle-axis, low-precision actuator (track system) to be utilized, withlow-cost sensors to confirm container pick-up and drop-off at individualmodules or on an overhead transport system.

The modular bioprocessing system 7500 may be similar to the modularbioprocessing system 7400 shown in FIG. 74 . The modular bioprocessingsystem 7500 may include one or more bioprocessing modules 7502 that hostcell culture containers. The example shown in FIG. 75 uses microwellplates 7508 as cell culture containers, but any suitable cell culturecontainer is compatible with the described implementation, such asclosed cassettes. A set of rails 7504 may be mounted on the rack front,allowing vertical motion control of a vertical transporter 7506 mountedon the rails 7504. A bioprocessing module 7502 may eject a microwellplate 7508 from the front of the module onto an extended containerinterface (e.g., container interface 7404). The vertical transporter7506 may approach the container interface from the bottom to retrievethe microwell plate 7508 from a bioprocessing module 7502 that ispresenting it. The vertical transporter 7506 may then transport themicrowell plate 7508 to another location along the vertical axis of therack and/or allow a person to collect the microwell plate 7508.Alternatively, the vertical transporter 7506 may approach an extendedcontainer interface from the top when it is delivering a microwell plate7508 to a bioprocessing module 7502, and the microwell plate 7508remains on the extended container interface as it passes. The containerinterface may then retract the microwell plate 7508 into the associatedbioprocessing module.

For single-rack installations, or multi-rack installations where theracks are independent, this vertical transport is sufficient tocompletely automate the bioprocessing system, again with an extremelycompact footprint compared to existing bio-automation configurations. Inthe case of multi-rack systems where automated microplate exchange isdesired between racks, or between individual racks and a fill/harvest orother central location, a horizontal track-based transporter 7510 isprovided. The horizontal transporter may transport cell culturecontainers in a horizontal axis of the rack. The horizontal transporter7510 provides a mechanical interface similar or identical to thecontainer interfaces, in order to hold the microplate wells 7508 fortransport. The vertical transporter 7506 may load microwell plates 7508onto the horizontal transporter 7510 by approaching from the top, orpicks up a plate from the horizontal transporter 7510 by approachingfrom the bottom. Neither the vertical nor horizontal transport systeminterfere with human operator access to the front (or back) of themodules, so plates may be manually retrieved or added by human operatorsin concert with automated transport. Moreover, the automated transportworks with minimal footprint, and may use low mechanical force toincrease safety.

FIG. 76A is another diagram of a modular bioprocessing system 7600 inaccordance with various implementations. In this implementation, thecell culture container is implemented as a cassette 7602 that may beused for various cell culture processes, including but not limited tocell reprogramming, cell differentiation, cell gene editing, and/orcell-based bioproduction. The cassette 7602 is sealed in order to allowsterile processing of multiple samples in the same environment, for ahigh degree of control and consistency, and potentially for goodmanufacturing practice (GMP) compliance for therapeutic (patient-bound)products. An example of the application of this implementation is theproduction of patient-specific human induced pluripotent stem cells(hiPSCs), and subsequent differentiation of hiPSCs into replacementcells for cell therapies. In such an application, complete isolation ofpatient samples from one another is required, and accomplished using acassette-based system where required media and reagents, as well aswaste reservoirs, are contained within a sealed liquid system on thecassette 7602. In this example, the cassette 7602 may include a cellculture chamber that is fully imagable, and the cell culture chamber isconfigured to allow selective laser ablation of cells from the cellculture, with subsequent removal of resulting debris by on-board liquidhandling subsystems. Using this combination of elements, a high degreeof control and therefore predictability and yield is possible to achievein a sealed cell culture.

The cassettes 7602 may be inserted into bioprocessing modules 7606mounted in a rack 7604, which may have standard server rack dimensions.The cassette hosts 7606 may provide a number of functions, such as (a)incubating the cells in the cassette inserted into the host; (b)actuating on-cassette liquid handling systems for media replenishment,reagent additions, waste removal; (c) monitoring media conditions in thecassette, for example dissolved oxygen and pH, and making adjustments asnecessary; (d) providing gas exchange with the on-cassette circulatedmedia to adjust oxygen and other dissolved gas levels; (e) imaging thecells within the cassette; (f) selectively destroying and ablate cellswithin the growth chamber using a laser system; and (g) editing cells(e.g., inserting cargo into a cell or removing cargo from a cell) withinthe growth chamber using a laser system. In this manner, a singlebioprocessing module 7606 may monitor and control a long-duration cellculture process without removal or transport of the cassette 7602,reducing the potential sources of variability in the process. Thebioprocessing modules 7606 in a rack operate independently but may sharea number of resources, as described below.

Shared computing, storage, and communications modules 7608 may be usedto process imagery acquired by each bioprocessing module 7606 fornormalization, registration, stitching, and other functions. Theresulting images/data may be further processed using a machine learningsystem that is located either locally or remotely (e.g., elsewhere onthe premises or in the cloud). Algorithmic choices or predictions maythen be computed internally or transmitted back to this computinginfrastructure to drive selective laser removal of cells within eachbioprocessing modules 7606 and associated cassette 7602. For example, ashared pulsed laser module 7610 may provide laser energy to multiplebioprocessing modules 7606 via standard fiber optic connectors locatedon the rear of the rack 7604. The energy may be split among thebioprocessing modules 7606 via a tree of static fiber optic splitters orswitched from unit to unit via an optical switch, or via some othermethod. In some implementations, there may be more than one laser modulein the modular bioprocessing system 7600. In some implementations, asingle laser module may be used for modules in multiple racks within themodular bioprocessing system 7600.

A shared environmental control module 7612 may be used to provide cellculture temperature control (usually 37° C.), reagent cooling (often 4°C.), laser cooling, and cooling for the data storage and computingmodules, especially in the case where local central processing units(CPUs) or graphics processing units (GPUs) perform large workloads forimage processing or machine learning operations. A shared power supply7614, in some implementations a power supply with built-in redundancy,may be used to provide reliable DC current to the bioprocessing modules7606, laser module 7610, and potentially the data storage and computingmodules, so that there is no need for individual power supplies.

The various implementations allow for small system configurations, asshown by the half-height setup 7616 with very small footprint and setuptime, and incremental addition of bioprocessing modules 7606 foradditional capacity as demand requires. The modular configuration alsoenables a high degree of redundancy and reliability because sparemodules may be added or brought online very quickly to compensate forany failures. In the example shown in FIG. 76A, a small modular system,even in a half-height rack, may take the place of several high-gradecleanrooms (often located in expensive urban spaces) for GMP cellculture, and negate the need for extensive suiting-up for personnel fordaily cell culture observation and manual modification/transfer steps.

The modular bioprocessing system 7600 illustrated in FIG. 76A may befitted with a transport system similar to the one described withreference to FIG. 75 , with simple, human operator-compatible verticalas well as horizontal transport for large multi-rack facilities. Themodular bioprocessing system 7600 may include other components notillustrated in FIG. 76A, and may include variations known to persons ofordinary skill in the art.

FIG. 76B shows an exemplary prototype process module (lower, withhandles) and partially inserted cell culture cassette, which is shownco-located with RAID storage array (with 16 drive bays visible) andbackup power module (above, marked Tripp Lite).

Hot-Swap Redundant Cell Culture Systems

Many cell culture processes, including gene editing, reprogramming (forexample, reprogramming cells into iPSCs), expansion, differentiation,and bioproduction, may require lengthy, complex processes. Cell culturesystems that run these processes may be complex and have many differentsubsystems, such as environmental sensors and controls, media/waste andreagent transfer subsystems (pumps, valves, sensors), imagingsubsystems, and cell editing and/or manipulation subsystems (includingdirected-energy systems for intracellular delivery or selective celldestruction or removal, cell culture washing systems, etc.). Thiscomplexity makes these systems prone to failures due to the failure of asingle component, subsystem, or software. In current systems, thisusually results in the loss of the cell culture, which may be extremelyexpensive and also have a large impact on patients awaiting the cellproduct.

Implementations disclosed herein, for example in FIGS. 74-76 , describethe use of a distributed, modular system, in which cell cultures areprocessed simultaneously in multiple modules that each encompass a rangeof functionality. These implementations reduce the chance of massfailures due to shared equipment (for example, robotic arms, imagingsystems, liquid handling systems, cell editing systems). Theseimplementations also prevent bottlenecks, for example if a transportrobot that is used to move cell cultures around the system fails orbecomes misaligned, or a central shared imaging subsystem fails due to asoftware issue. However, even modular systems may fail, and though thisfailure impacts only a single cell culture in process, it would behighly desirable that the failure of a cell culture module does notresult in the failure, destruction, or denaturing of the cell culturebeing handled by the module.

In some cases, cell culture processes may require a diversity ofprocesses that cannot practically be accomplished within a single cellculture system. Current systems require at least tubing and otherreconfigurations, if not cell material transfers, to achieve suchchange-overs, resulting in more complex processes, more manual steps,higher probabilities of damage to the cell culture, or contamination.

The systems and methods disclosed herein include a cell culture systemin which components may easily be switched out and replaced so that thecell culture system may easily be adapted for different cell cultureprocesses and also to allow for easy repairs. The cell culture systemmay include a cell culture container (e.g., a closed cassette system)that includes at least one cell culture chamber and supportingcomponents. All fluidic paths, including the cell culture chamber(s),may be sealed for at least a portion of the cell culture process toensure sterility and prevent cross-contamination. The cell culturecontainer may also include on-board media, reagents, buffers, product,and/or waste reservoirs and tubing components. The cell culturechamber(s) may be configured to allow imaging of the cell culture andallow directed-energy editing (e.g., intracellular delivery or lysis) ofthe cell culture.

The cell culture container (which may be a closed cell culture cassettein some implementations, as described with reference to FIGS. 67-73 )may be quickly connected and disconnected to external components throughconnection plugs so that the cell culture container may be plugged into,or removed from, a modular bioprocessing system which manages the cellculture container and cell culture conditions. These connections mayinclude electronic connections (e.g., for power, sensor readouts, valveor pump actuation), communication connections (e.g., forprocessor-to-processor communication), and liquid or gas connections(e.g., for temperature control of the cell culture and/or media,reagent, buffer, waste, product containers on board the cell culturecontainer, or dissolved gas control). The liquid path inside the cellculture container may be self-contained and non-accessible to preserve aclosed loop and keep the cell culture container sterile.

The cell culture system may also include process module(s) that receiveone or more cell culture containers and provide cell culture supportfunctions. The process modules may be configured so that the cellculture containers may hot-plug into the process module using theconnectors to provide monitoring and support to the cell culturecontainers. The process module and cell culture containers may bedesigned so that if the process module fails or malfunctions, the cellculture containers may be removed from the process module via a simplemechanism, for example a mechanical unlock and subsequent pull.

The cell culture system may also include a computing and communicationsystem that monitors and tracks the status of each cell culturecontainer as it undergoes a cell culture process recipe. The system mayessentially maintain a “digital twin” of the cell culture container(e.g., a dynamic digital profile of the cell culture) that may be storedon the cell culture container, and/or on a remote server. This allows acell culture container to be removed from one process module andinserted into another without any data entry, and allows the receivingprocess module to quickly resume the cell culture process withappropriate conditions (temperature, media exchange, reagent or bufferadditions, dissolved gas control, flow rate/liquid shear control,washing or agitation, etc.). For example, the cell culture container maycontain non-volatile memory such as FLASH memory that contains a recordof the cell culture process recipe, as well a history of what steps havebeen performed, and conditions on the cell culture container. Thus ifthe cell culture container is removed from one process module andinserted into another, the process module may read this memory andproceed with the current or next steps of the cell culture protocolunder the correct conditions. In some implementations, the cell culturecontainer includes a barcode or an electronic tag (which could includenonvolatile memory on board) that presents a container ID to the processmodule, and the process module retrieves a process recipe and historyfrom a server when the container is inserted, so that it may immediatelyresume the process.

FIG. 77 is a diagram of a modular cell culture system 7700 in accordancewith various implementations. The modular cell culture system 7700 maysupport a number of cell culture containers, which may be formatted as aclosed cell culture cassette 7702 (e.g., closed cassette system 6700).The cassette 7702 may have a housing that includes a handle 7704. Thehousing encloses one or more compartments 7706 for carrying cell culturemedia, reagents, waste, cell products, etc., as well as a liquidhandling system to circulate media, waste, debris, cell products, etc.,into and out of a one or more cell culture chambers 7708. The cellculture chambers 7708 may be suited for culturing of suspension and/oradherent cells. The cell culture chambers 7708 may further be configuredfor imaging of the cell culture (e.g., label-free imaging through atransparent surface of the cell culture chambers 7708) and directedenergy editing of the cell culture (e.g., using cell editing subsystem114).

The modular cell culture system 7700 may include a series of cellculture process module 7710, each of which are configured to receive thecassettes 7702. Each process module 7710 may be configured to manage thecell culture functions on the cassette 7702 docked in that particularprocess controller 7710. These functions include, but are not limitedto, temperature controls (e.g., for cell cultures, and for media,reagents, products, and waste, which may each be controlledindependently or in groups), cell media and/or reagent addition andcirculation, cell culture washing or harvest, control of dissolved gasconcentrations, control of pH, imaging of the cell culture, and directedenergy editing of the cell culture (e.g., laser editing).

The process module 7710 interfaces to the cassette 7702 via plug sockets7712 for electrical, communications, gas, temperature control and otherconnections. These plug sockets 7712 may be configured such that acassette 7702 may be quickly loaded or unloaded from the process module7710 without manual connection or disconnection of wires or tubes, or insome cases even without execution of software programs and associatedfunctions in the containing cell culture module, so a “hot swap” may beperformed to move cassettes 7702 from one process module 7710 toanother. An on-board computer 7714 in the process module 7710 mayconnect electronically with an on-board computer or memory of thecassette 7702, or read a barcode on the cassette to ascertain theidentity and retrieve the current operating state of the cassette 7702.

The process module 7710 communicates via a communications network 7716to a cassette data monitoring system 7718 which maintains a cassettestate database 7720. The cassette state database 7720 stores a “digitaltwin” for each cassette 7702 in the modular cell culture system 7700,the digital twin reflecting the current cassette status and intendedcell culture process. Thus if a cassette 7702 is pulled from one processmodule 7710 and inserted into another, the receiving process module 7710can immediately resume the desired cell culture program for the cassette7702.

This allows a cassette 7702 to be moved quickly in case of a malfunctionin a process module 7710 or supporting infrastructure, or moved around afacility depending on the stage of a cell process. The process modules7710 may also communicate with a module monitoring system 7722 whichmaintains a process module “digital twin” database 7724 to monitorcritical module functions and detect any deviations. Additionally, themodule monitoring system 7722 may be used when a process module 7710 ismoved from one process cluster or facility to another, or from one setof supporting systems to another.

The modular cell culture system 7700 may include supporting subsystems7726 that are shared by multiple process modules 7710. Supportingsubsystems 7726 may include, but are not limited to, environmentalcontrol systems (e.g., for providing warming for cell cultures and/orcooling for media, reagents, products, and computing or opticalsubsystems), laser systems for directed-energy editing of cell cultures,cell culture imaging, autofocus or registration functions, and/orspectral sensing of media or cell cultures, power supply systems (e.g.,an internally redundant 24 VDC power supply), and computing systems forcomputing or storage associated with imaging, spectral sensing, cellculture editing, etc. (which may also have internal redundancies). Thesupporting subsystems 7726 are connected to the process modules 7710 viapluggable or quick connectors 7728 to facilitate easy connection ordisconnection of the process modules 7710 from a local cluster, forexample a cluster of process modules 7710 on a server rack along withsupporting subsystems 7726. The supporting subsystems 7726 typicallyhave embedded computers or sensing/computing modules 7730 to monitorand/or control these subsystems.

One or more supporting subsystem monitoring services 7732 may monitorthe supporting subsystems 7726 and tracks performance in a supportingsubsystem database 7734, again establishing a “digital twin” for eachsupporting subsystem 7734 for redundancy and quick-resume functions. Ifa supporting subsystem 7726 indicates a problem it may be quicklyreplaced and cell processes continued, or the affected cassettes 7702may be moved to process modules 7710 on another set of functioningsupporting subsystems 7726, and/or one or more process modules 7710 maybe moved to a new set of functioning supporting subsystems 7726.

The modular cell culture system may also include a cell culturemonitoring system 7736 configured to tracking the cell culture state ineach cassette 7702 (and in turn the cell culture chambers in eachcassette) and maintains a cell culture database 7738 that stores a“digital twin” of each cell culture (which may include time seriesimages, cell or colony feature databases, sensor data streams, etc.).Finally, an overall monitoring and control system 7740 may be configuredto monitor the overall modular cell culture system 7700, bycommunicating with the monitoring systems 7718, 7722, 7732 and 7536, andcoordinates responses to failures or states requiring attention, forexample transfer of cassettes 7702 from one process area to another. Themodular cell culture system 7700 may include other components notillustrated in FIG. 77 .

The process modules 7710 may have different configurations correspondingto different cell culture processes, or stages of these processes. Thusthe ability to pull cassettes 7702 from one process module 7710 andplace them in another while maintaining continuity in cassetteconditions, environmental parameters, and cell culture data andprocesses enables very efficient, failure-free multi-stage cell cultureprocesses. In addition, the modular cell culture system 7700 is veryflexible as it can accommodate different cell culture processesperformed in parallel, which increases throughput while minimizingdelays in equipment failures or other issues.

FIG. 78 is a diagram of a cell culture cassette 7800 compatible with amodular cell culture system in accordance with various implementations.The cell culture cassette 7800 is an example implementation of a cellculture container (e.g., cell culture container 106) in a cell culturesystem. The cassette 7800 may be primarily designed for 2D adherent cellcultures. The cassette 7800 may include a 2D liquid cell culture chamber7802 with transparent upper and lower surfaces, which may be used forimaging and directed-energy editing of the cell culture. Mechanicalguide rails 7804 serve to align the cassette 7800 to the process moduleas it is inserted. As it is inserted, connectors 7806 plug intocomplementary connectors on the process module. These connectors carryelectrical signals, including but not limited to any required power,communications, signals from sensors aboard the cassette, and controlssignals to actuators aboard the cassette. The connectors 7806 may alsoinclude non-mechanical elements such as gas or liquid ports. Forexample, cooling or warming liquids may flow in a loop through theconnectors 7806, or gases for maintaining proper dissolved gasconcentrations may flow in a loop through the connectors 7806. In thesecases, quick-connect fittings may be used to seal the connections upondisconnection of the cassette 7800, and open them when the cassette 7800is inserted.

The connectors 7806 may be disengaged mechanically through a lockingmechanism accessible from the front of the cassette 7800 or processmodule (possibly on or near handle 7808), or electromechanically by theprocess module. The cassette 7800 may be removable from the processmodule regardless of software, electrical, or other failures in theprocess module, so the cassette 7800 may be quickly withdrawn usinghandle 7808 and placed in another process module. In the example shownin FIG. 78 , the cassette 7800 may include two independent storagecompartments for maintaining liquids associated with the cell culture,including but not limited to cell media, reagents, buffers, cellproducts, and waste, which may be stored in sealed bags or othercontainers. For example, one compartment 7810 may store media andreagents at 4° C., while another compartment 7812 may store cellproducts at 37° C. Temperature control ports 7814, which are sealed whenthe cassette 7800 is not in a process module, may be pushed open by theinsertion of the cassette 7800 into the process module. This allows theprocess module to push temperature-controlled air through thecompartments 7810, 7812 perpendicular to the plane of the cassette 7800.Thus, each compartment 7810, 7812 may be preciselytemperature-controlled in a closed-loop fashion while in the processmodule, but when the cassette 7800 is pulled from the process module theports 7814 may close automatically, such that temperature withincompartments 7810, 7812 may maintained passively while the cassette 7800is in transit or awaiting transfer to another process module.

In some implementations, the cassette 7800 may be designed to allow anoptical system to access the cell culture chamber 7802 for the purposeof imaging the cell culture (e.g., cell imaging subsystem 112) and/orediting the cell culture through a cell editing mechanism such as usingdirected energy (e.g., cell editing subsystem 114). The directed energyediting may take the form of laser light, ultrasound, magnetic toolsinside the cell culture chamber 7802 that are directed by externalmagnetic actuators, or other methods. The cell imaging and cell editingsubsystems may interact with the cassette 7800 without physicalentanglement such that it may be manually withdrawn from the processmodule without damage to the cassette 7800 or process module when anysubsystem fails. The cell imaging and cell editing subsystems may alsobe configured to return to an “off” mode in case of a software, power,or mechanical failure in the process module, for example cutting offlaser illumination, cutting off imaging illumination, and retractingmagnetic actuators though a “active-on” solenoid or compressed-airmechanism.

In the case that a failure is detected in the process module, an “eject”sequence may be activated which unlocks the cassette 7800 and pushes itpartially out of the process module. The partial ejection may includedisengaging all ports and connectors 7806, to close all valves on boardthe cassette 7800, to stop pumping on board the cassette 7800, and toseal all temperature control ports 7814 (liquid or gas). This may beachieved, for example, by solenoid and spring actuators that areretracted electromagnetically when the process module is active andrunning properly and a cassette 7800 is inserted, but when there is afailure detected in the process module, or power is lost, spring back toeject the cassette 7800 into retraction position. In this position, thecell culture is effectively in a “safe” mode where liquid is not flowingand temperatures are maintained passively until it may be moved to anactive process module.

FIG. 79 is a diagram of a cell culture cassette 7900 compatible with amodular cell culture system in accordance with various implementations.The cell culture cassette 7900 is an example implementation of a cellculture container (e.g., cell culture container 106) in a cell culturesystem. The cassette 7900 may be primarily designed for suspension cellcultures held in a miniature stirred tank bioreactor, with a steriletubing set connecting it to cell media, buffers, reagents, and alsowaste and cell product bags that are all stored on-board. Guide rails7902 allow the cassette 7900 to be inserted into a corresponding processmodule and assure mechanical alignment of plug connector ports includingelectrical/communications connectors 7904 and gas/liquidquick-connectors 7906. In some implementations, when inserted, amagnetic actuator on the process module aligns with a follower magneticcomponent 7908 which is connected to the stirrer in the cell culturevessel. However, in general any number of non-contact methods ofstirring the interior of the cell culture vessel may be implemented inthe cassette 7900. For example, other implementations may includemagnetic couplings to actuate valves on the cassette 7900, operateperistaltic pumps on the cassette 7900, or move actuators within thesealed cell culture vessel for the purpose of washing cell cultures,circulating media, or removing cells or debris from surfaces.

A latch 7910 may be used to lock the cassette 7900 in place in theprocess module, and may be mechanically coupled to a number ofcomponents to open/close them appropriately, including but not limitedto the gas/liquid ports 7906. The latch 7910 may be opened prior toretrieving the cassette 7900, assisted by handles 7912. A display on thecassette 7900 may display the current status of the cassette 7900 andcell process, and may include touchscreen functions.

In the implementation shown in FIG. 79 , two compartments 7914 areconfigured to carry media, reagents, buffers, cell sources, and waste,cell products, etc. However, in general there may be any number ofcompartments 7914. The compartments 7914 may be temperature controlledvia air ports 7916 on the side of the cassette 7900. For example, theair ports 7916 may be used for entry (top) and exit (bottom) oftemperature-controlled air from the process module to keep the left-sidecompartment to 4° C. temperature. The air ports 7916 may be configuredto close when the cassette 7900 is not fully-docked to the processmodule, to maintain the internal temperature of the compartments 7914 aslong as possible. Similarly, the air ports 7916 corresponding to thebioreactor may be used in either in top-to-bottom or side-to-sideconfiguration to move air through the bioreactor enclosure and maintainits temperature, typically at 37° C.

FIG. 80 is a diagram of a rack-style modular cell culture system 8000 inaccordance with various implementations. The modular cell culture system8000 may include any number of cell culture process modules 8002 (eightshown in FIG. 80 ) and several supporting modules mounted in aserver-style rack 8004. The process modules 8002 may be configured toreceive a cell culture cassette 8006 (shown in insertion/retractionposition in FIG. 80 ), which may be similar to cassette 7800 in FIG. 78for 2D adherent cell cultures.

The modular cell culture system 8000 may include a shared environmentalcontrol module 8008. In an example implementation, the sharedenvironmental control module 8008 may circulate refrigerant and twotemperatures, for example 0° C. and 40° C., along liquid manifoldscontained in an environmental control column 8010. The environmentalcontrol column 8010 provides process modules 8002 with thermal “rails”to maintain temperatures for cell culture and various media, reagent,waste, or cell product compartments. It also provides components thatgenerate significant heat (for example, computing modules, if present,or shared laser modules) with cooling, while maintaining a compactfootprint (as opposed to air-cooling each one). The environmentalcontrol module 8010 may exchange heat between the return streams, andmay also include high-flow air circulating through it for heat exchangepurposes, through ducts 8012.

The modular cell culture system 8000 may also include a computing andcommunications module 8014 that provides local computing, storage andnetwork communications (e.g., computing subsystem 110). In an exampleimplementation, multimode fiber and optical transceivers may be used toprovide communication between the computing and communications module8014 and individual process modules 8002, ensuring high bandwidth duringcell culture imaging. The computing and communications module 8014 mayalso provide local processing and storage of the images, and potentiallycomputing of cell culture editing functions. The computing andcommunications module 8014 may also be connected to external networksvia fiber optics or other communications links that pass through a duct8016. External networks may store “digital twins” of process modules8002, cassettes 8006, and supporting modules 8008, 8014, 8018 in themodular cell culture system 8000. These digital twins may aid inmonitoring and tracking cell culture, cassette, and process modulestatus and performance versus nominal, and provide hot-swap capabilityin the case of failure of a process module or any supporting system.

The modular cell culture system 8000 may also include a cell editingsubsystem, such as a shared pulsed laser system 8018. Pulsed laser lightfrom the pulsed laser system 8018 may be transmitted via optical fiberto each process module 8002. For example, the pulsed laser system 8018may include a nanosecond pulsed laser with 532 nm or 1064 nm emission.The laser light may be split into eight equal power beams (may beachieved using free-space optics, or fiber optic couplers), and coupledinto polarization-maintaining single-mode fiber. These fibers are routedto respective process modules 8002. Each process module 8002 may beconfigured to synchronize to the pulse timing (for example, 500 kHz) andthen apply modulation (for example, with an acousto-optic modulator) andbeam steering for the purpose of directed-energy cell culture editing.In other implementations, laser sources may be shared for otherpurposes, such as illumination for fluorescent, auto-fluorescent,two-photon imaging, Raman spectroscopy, or other sensing modalitieswithin the cell culture modules. The modular cell culture system 8000may also include a shared DC voltage power rail to provide power to theentire rack 8004 and supported equipment, fed by power duct 8020. Inalternate implementations, DC power supplies may be mounted on the rack8004 itself as rack-mounted equipment (potentially with connections forcooling).

Methods of Manufacturing Semi-Adherent Cells and Cell Products

The immune system is divided into two systems: the innate immune system,which acts rapidly and generally, and the adaptive immune system, whichrepresents an acquired immune response and is much slower and specific.In recent years, cell-based immuno-oncology therapies, including but notlimited to adoptive cell immunotherapies, have risen dramatically.Immune system cells are naturally capable of recognizing and eliminatingentities which do not belong in the body, so they are effective vehiclesto treat various diseases. These strategies may involve modifications ofthe immune system cells to improve recognition and elimination oftumors. Examples include tumor infiltrating lymphocytes (TILs), chimericantigen receptor (CAR) T-cells, T-cell receptor (TCR) therapies, andactivated dendritic cells (DCs), macrophages, or some mix of these orother immune-related cells. It is widely recognized that the safest andmost effective therapies would be autologous, which are derived from thepatient's own cells which respond uniquely to tumor cells, reducing oreliminating toxicity and need for immunosuppression.

However, there are several hurdles to utilizing autologous immune celltreatments. Cells may be difficult or painful to isolate (especially innumbers viable for therapeutic doses), dysfunctional, functionallycompromised, variable in capability, difficult to consistentlygenetically modify, have limited in vivo survivability and migratorycapability, require repeated harvesting or dosing, and are challengingto manufacture under good manufacturing practice (GMP) conditions, amongother limitations.

As an example, dendritic cells (DCs), the most powerful of the antigenpresenting cells, are widely considered the bridge between the innateand adaptive immune systems by identifying threats and acting asmessengers. DCs signal to T-cells via surface receptors and secretedcytokines to dictate various T-cell responses. Due to their unique rolein the immune system, DCs have powerful therapeutic potential both ininducing immunity, such as with oncology, and in tolerance, such as withautoimmune diseases. They are a rare cell type in human blood, <0.1% ofblood, which makes it challenging to harvest adequate primary cellnumbers for therapy. Additionally, there are various DC subsetsincluding conventional DC Type 1 (cDC1), conventional DC Type 2 (cDC2),plasmacytoid DCs (pDCs), and monocyte-derived DCs (moDCs), which arespecialized for various conditions and applications. DCs are sensitiveto an immuno-suppressive tumor microenvironment and thus theiractivation may be suppressed in vivo. Furthermore, DCs require anautologous approach to maximize functionality as T-cells recognizepeptides bound to MHC receptors on DCs, particularly class II receptors,but there can be variability in the primary cell source.

Due to limited source material and cell sensitivity, the majority ofclinical trials to date have involved autologous moDCs. This subset isfar from optimal, most commonly found in inflammatory conditions, withlimited cross-presentation and migratory capability. The rarest of theDC subsets, cDCis, represent <0.03% of peripheral blood mononuclearcells and are highly effective at cross-presentation to T-cells.However, this subtype has yet to be clinically explored in earnestlargely due to limited in vivo numbers, difficulty of isolation inblood, and the ease with which moDCs can be derived. Further, it isplausible that all DC subsets could be further optimized through geneticor non-genetic modification, including but not limited to cell viabilityin vivo, migratory capabilities, cross-presentation capability, andmaturation or activation level.

Large-scale manufacturing of induced pluripotent stem cells (iPSCs)which can then be differentiated to the immune cells of interestrepresent an elegant solution to issues noted above. They can becultured unlimitedly in vitro, successfully differentiated towards thelymphoid lineage, are easily amenable to genetic transformations invitro, and consistency may be achieved through fully modified andquality controlled clonal lines. The terminally differentiated productmay be edited in order to optimize for purity and functionality. Thuswhat is needed in the art are systems and methods for large scalegeneration of semi-adherent cells, which include immune cells,particularly as an extension of large scale manufacturing of iPSCs.

The systems and methods disclosed herein include an automated researchand clinical-grade manufacturing system for various semi-adherent cells(e.g., immune cells such as dendritic cells) which (1) allows 100%non-contact measurement of semi-adherent cells and semi-adherentcell-based therapies in culture, starting first from a primary cellsource, reprogramming to a progenitor cell type such as human inducedpluripotent stem cell (hiPSC) or CD34+ hematogenic progenitor cells, inorder to monitor and control the biomanufacturing process; (2) enablesselective combination, segregation and isolation of the various cellpopulations or subpopulations and maturity levels as specified for theend product; (3) enables genetic modification of cells or theirprecursors to optimize the end product: and (4) is sealed in a mannerthat allows parallel manufacture in a non-sterile facility, and further,in some cases, allows editing of cell cultures based on image-derivedcharacteristics.

Such a system would enable a wide range of cell biomanufacturingprocesses at a scale, consistency, yield and cost that are notachievable in the prior art, including through selectivity in subset,generation of enough viable cells for a therapy (estimated ˜10⁵ to 10⁸cells per dose over approximately 1-10 injections), the elimination ofany cells or material which lowers the quality of the final product(including but not limited to unwanted cells or undifferentiated cells),enabling of multiple and/or reduced dosing due to autologous nature oftherapy, and the correct maturation or activation level. This capabilityis particularly important to translate emerging patient-specificdendritic cell therapies from the laboratory to clinical trials andultimately to larger patient populations. An automated system would notrequire any handling, enable genetic manipulation of a sensitive cellpopulation, and avoid undesired biological consequences, such as cellactivation prior to need. The system may be applicable to numerousimmune cells and more generally to any kind of semi-adherent cells.

FIGS. 81A-83C are diagrams illustrating cell culturing in a closed cellculture chamber in accordance with various implementations. FIG. 81Ashows a microfluidic cell culture cavity 8102 in a cell culture chamber,which may be part of a closed cell culture container (e.g., cell culturecontainer 106 in FIG. 1 ) in a cell culture system. The cell culturecavity 8102 may be enclosed by top and bottom surfaces 8104 and sidesurfaces (not shown in FIG. 81A). The cell culture cavity 8102 may beconnected to one or more fluid reservoirs (not shown) to enable fluidflow into and out of the cell culture cavity 8102, for example torefresh fluid media in the cell culture cavity 8102 or to flush one ormore cells or debris from the cell culture cavity 8102. There may be aperfusion flow 8106 of fluids through the cell culture cavity 8102. Theparameters of the perfusion flow 8106 may be controlled by a controlsystem (e.g., computing subsystem 110 in FIG. 1 ). For example, thecomputing subsystem may control the flow rate of the perfusion flow 8106and may turn the perfusion flow 8106 on and off to enable variousfunctionalities as further described herein.

FIG. 81B shows the cell culture cavity 8102 of FIG. 81A, except that thetop and bottom surfaces 8104 of the cell culture cavity 8102 may becoated with an absorption layer 8108 on the outside of the cell culturecavity 8102. The absorption layer 8108 may be configured to absorbpulsed laser light 8110 impinging on the cell culture cavity 8102 whileallowing other light to pass through in order to image the contents ofthe cell culture cavity 8102. When a pulsed laser light strikes impingeson the cell culture chamber 8102, it may create microbubbles 8112 on theinside of the cell culture chamber 8102. The microbubbles 8112 maycollapse to create shockwaves within the cell culture chamber 8102,which may be used to impart mechanical forces in the local environment.For example, the microbubbles 8112 and subsequent shockwaves may be usedto mix the fluid media, knock adhered cells loose from the impingingsurface, destroy adhered cells, or weaken cell membranes to allowtransport of pay loads into and out of cells. The pulsed laser light8110 may be controlled by a computing subsystem or other control systemin a cell culture system.

FIG. 81C shows the cell culture cavity 8102 of FIG. 81A with adherentcells 8114 growing on the top surface of the cell culture cavity 8102.The adherent cells 8114 may be immune system cells, such as macrophages.The cell culture cavity 8102 may be oriented so that the force ofgravity acts downwards in FIG. 81C. This may be termed an invertedorientation. For example, cells may be initially cultured on the bottomsurface of the cell culture cavity 8102. When the cells become adherentcells 8114, the cell culture cavity 8102 may be inverted or flipped suchthat the adherent cells 8114 rest on the now top surface of the cellculture cavity 8102 as shown in FIG. 81C.

The cell culture cavity 8102 may also include semi-adherent cells 8116,which may be monocytes or dendritic cells for example. Semi-adherentcells 8116 may have a weaker adherent bond to the top surface of thecell culture cavity 8102 than adherent cells 8114. The cell culturecavity 8102 may also include non-adherent cells 8118 that have detachedfrom the top surface. The non-adherent cells 8118 may be, for example, Tcells or dendritic cells that have been naturally or artificiallyreleased from the top surface. For example, pulsed laser light 8110 maybe used to knock cells loose from the top surface so that they becomenon-adherent cells 8118.

The cell culture cavity 8102 may also include bottom restingnon-adherent cells 8120. The non-adherent cells 8120 may be non-adherentcells 8118 that come to rest on the bottom surface due to gravity. Thecell culture cavity 8102 may also include re-adhered cells 8122, whichare bottom resting non-adherent cells 8120 that adhere to the bottomsurface of the cell culture cavity 8102 if they are allowed to remainthere for a period of time.

FIGS. 82A-82B are diagrams illustrating adherence of cells in a closedcell culture cavity in accordance with various implementations. FIG. 82Aillustrates a closed cell culture cavity, which may be similar to cellculture cavity 8102 in FIGS. 81A-81C. The cell culture cavity mayinclude an adhering surface 8202, which is the bottom surface as shownin FIG. 82A. Adherent cells 8204 may be adhered to the adhering surface8202. The adherent cells 8204 may be various types of immune cells, suchas macrophages, dendritic cells, and T cells, and may have varyingdegrees of adherence to the adhering surface 8202. The adherent cells8204 may be introduced to the cell culture cavity and given some time toadhere to the adhering surface 8202. The cell culture cavity may alsoinclude one or more non-adherent cells 8206 that come to rest on but arenot adhered to the adhering surface 8202 due to gravity.

At a certain time, the cell culture cavity may undergo inversion 8208such that the adhering surface 8202 is now the top surface and the forceof gravity acts downward, as shown in FIG. 82B. A computing subsystemmay invert the cell culture cavity in response to certain criteria. Forexample, inversion may happen after imaging shows that a certain numberor percentage of cells are adhered, or when adhered cells show certainproperties, or at a predetermined point in time from the start of thecell culturing process. The cell culture chamber containing the cellculture cavity may be connected to one or more actuators that carry outthe inversion motion and that are controlled by a computing subsystem.After inversion 8208, the adhered celled 8204 may remain on the adheringsurface 8202 while the non-adherent cells 8206 may fall to the oppositesurface due to gravity.

FIGS. 83A-83E are diagrams illustrating separation of adherent andsemi-adherent cells in a cell culture cavity in accordance with variousimplementations. FIG. 83A illustrates a closed cell culture cavity,which may be similar to cell culture cavity 8102 in FIGS. 81A-81C. Thecell culture cavity may be part of a cell culture system (e.g., cellculture system 100). The cell culture cavity may include an adheringsurface 8302 upon which rest adherent cells 8304 and semi-adherent cells8306. The adherent cells 8304 and semi-adherent cells 8306 may includevarious immune cells, such as T cells, dendritic cells, and macrophages.The cell culture cavity may be in an inverted orientation such that theforce of gravity points downwards in FIGS. 83A-83E, as described withrespect to FIG. 82B. The adhering surface 8302 may also have anabsorption layer on top of the adhering surface 8302, on the outside ofthe cell culture cavity, that absorbs pulsed laser light impinging onthe outside of the cell culture cavity.

The semi-adherent cells 8306 may be detached from the adhering surface8302 and separated from the adherent cells 8304 using a variety of cellediting mechanisms, as illustrated in FIGS. 83B-83E. The mechanisms mayinclude directing energy towards the adherent cells 8304 to dislodgethem. The energy delivered may include, for example, laser radiation,mechanical forces, and ultrasound. For example, in FIG. 83B a fluid flow8308 through the cell culture cavity may create lateral forces thatdetach the semi-adherent cells 8306 from the adhering surface 8302. Thefluid flow 8308 may be controlled by a computing subsystem and may beperformed at specific times or based on conditions within the cellculture cavity as measured by an imaging subsystem or by cell mediameasurements conducted by other components in a cell culture system. Thedetached semi-adherent cells 8306 may be pushed by the fluid flow 8308to another location in order to separate them from the adherent cells8304.

In another implementation as shown in FIG. 83C, an agitation tool 8310may be used to create local fluid flows that detach the semi-adherentcells 8306. For example, the agitation tool 8310 may be a magnetic toolthat is capable of translation across the bottom surface of the cellculture cavity and rotation as well. Rotation of the magnetic tool maycreate local forces that act on the semi-adherent cells 8306 and detachthem from the adhering surface 8302. The magnetic tool inside the cellculture cavity may be magnetically coupled to another magnetic tooloutside the cell culture cavity, which may be used to move the internalmagnetic tool. A computing subsystem may be configured to determine thelocation of the magnetic tool using imaging tools and control theexternal magnetic tool using one or more arms or actuators. In general,the agitation tool 8310 may be any tool that is controllable in order toloosen and detach semi-adherent cells 8306 from the adhering surface8304. The detached semi-adherent cells 8306 may then be pushed by theagitation tool 8310 or another mechanism to another location in order toseparate them from the adherent cells 8304.

In another implementation as shown in FIG. 83D, pulsed laser light 8312may impinge the outside of the adhering surface 8304. The pulsed laserlight 8312 may generate one or more microbubbles 8314 within the cellculture cavity. The microbubbles 8314, when collapsed, may create ashockwave that detaches the semi-adherent cells 8306 from the adheringsurface 8302, as described with respect to FIGS. 81A-81C. The detachedsemi-adherent cells 8306 may then be pushed to another location in orderto separate them from the adherent cells 8304.

In another implementation as shown in FIG. 83E, pulsed laser light 8316may impinge the bottom surface of the cell culture cavity. The pulsedlaser light 8316 may come from the top as shown in FIG. 83E, but mayalso come from the bottom of the cell culture cavity (not shown in FIG.83E). If the pulsed laser light 8316 originated from the top, theadhering surface 8302 may not have an absorption layer, or may have anabsorption layer that is configured to not absorb pulsed laser light8316 (e.g., at specific wavelengths). The pulsed laser light 8316 maygenerate one or more microbubbles 8318 within the cell culture cavity.The microbubbles 8318, when collapsed, may create a shockwave thatdetaches the semi-adherent cells 8306 from the adhering surface 8302, asdescribed with respect to FIGS. 81A-81C. The detached semi-adherentcells 8306 may then be pushed to another location in order to separatethem from the adherent cells 8304.

FIGS. 84A-84E are diagrams illustrating removal of semi-adherent cellsin a cell culture cavity in accordance with various implementations.FIG. 84A illustrates a closed cell culture cavity, which may be similarto cell culture cavity 8102 in FIGS. 81A-81C. The cell culture cavitymay be part of a cell culture system (e.g., cell culture system 100).The cell culture cavity may include an adhering surface 8402 upon whichrest adherent cells 8404. Semi-adherent cells 8406 may have beenpreviously detached from the adhering surface 8402, as described withrespect to FIGS. 83A-83C.

The adherent cells 8404 and semi-adherent cells 8406 may include variousimmune cells, such as T cells, dendritic cells, and macrophages. Thecell culture cavity may be in an inverted orientation such that theforce of gravity points downwards in FIGS. 84A-84E, as described withrespect to FIGS. 82A-82B. The adhering surface 8402 may also have anabsorption layer on top of the adhering surface 8402, on the outside ofthe cell culture cavity, that absorbs pulsed laser light impinging onthe outside of the cell culture cavity.

The semi-adherent cells 8406 may be removed from the cell culture cavityusing a variety of approaches, as illustrated in FIGS. 84B-84E. Forexample, in FIG. 84B a fluid flow 8408 through the cell culture cavitymay push the semi-adherent cells 8406 to another location, for example asecond cell culture cavity, a waste receptable, or a collectionreceptable. In some implementations, the cell fluid media containing thesemi-adherent cells 8406 may be filtered as it is moved to anotherlocation. The filtering may be done, for example, to separate cell fromcell debris, or separate cells by size, volume, mass, or othercharacteristics. The cell fluid media may be filtered using a number ofmethods, including but not limited to tangential flow filtration,ultrasonic separation, inertial microfluidic focusing, and deterministiclateral displacement using microfluidic features. A computing subsystemmay be configured to control the fluid flow 8308.

In another implementation as shown in FIG. 84C, a collection tool 8410may be used to push the semi-adherent cells 8406 to another location.The collection tool 8410 may be the agitation tool 8310 described withrespect to FIG. 83C, or may be a separate tool. For example, thecollection tool 8410 may be a magnetic tool that is controlled by anassociated magnetic component located outside the cell culture cavity.The collection tool 8410 may rest on the bottom surface and may push thesemi-adherent cells 8406 that are resting on the bottom surface towardsanother location. The collection tool 8410 may be controlled by acomputing subsystem.

In another implementation as shown in FIGS. 84D-84E in which theadherent cells 8404 may be destroyed, the semi-adherent cells 8406 mayhave adhered to the bottom surface of the cell culture cavity. The cellculture cavity may undergo inversion 8412 such that the semi-adherentcells 8406 are now on the top surface, as shown in FIG. 84E. Theadhering surface 8402 containing the adherent cells 8404 may now be thebottom surface. One or more laser pulses 8414 may target the adherentcells 8404. For example, a computing subsystem may determine thelocation of the adherent cells 8404 using an imaging subsystem, andcontrol a laser to target the adherent cells 8404. The laser pulses 8414may come from the top (as shown in FIG. 84E) of the cell culture cavity,or from the bottom. The laser pulses 8414 may create one or moremicrobubbles 8416 that lyse, or destroy, the adherent cells 8404. Afterthe adherent cells are lysed into cell debris 8420, a fluid flow 8418may push the cell debris out of the cell culture cavity. The computingsubsystem may control the fluid flow.

FIGS. 85A-85E are diagrams illustrating selective separation ofsemi-adherent cells in a cell culture system in accordance with variousimplementations. The semi-adherent cell culturing process may includemultiple steps, some of which were described in detail with respect toFIGS. 81A-81E. FIG. 85A illustrates a closed cell culture cavity, whichmay be similar to cell culture cavity 8102 in FIGS. 81A-81C. The cellculture cavity may be part of a cell culture system (e.g., cell culturesystem 100). The cell culture cavity may include an adhering surface8502 upon which rest a first plurality of cells 8504 having a first celltype/state and a second plurality of cells 8506 having a second celltype/state. The first and second plurality of cells 8504, 8506 may beone or more kinds of immune cells, such as T cells, dendritic cells,myocytes, and macrophages. The first and second cell types/stages of thefirst and second plurality of cells 8504, 8506 may be different types orstages of semi-adherent cells. For example, the first cell type/stagemay be a dendritic cell and the second cell type/stage may be amonocyte. In another example, the first cell type/stage may be animmature dendritic cell and the second cell type/stage may be a maturedendritic cell. The cell culture cavity may be in an invertedorientation such that the force of gravity points downwards in FIGS.85A-85E. The adhering surface 8502 may also have an absorption layer ontop of the adhering surface 8502, on the outside of the cell culturecavity, that absorbs pulsed laser light impinging on the outside of thecell culture cavity.

In FIG. 85B, pulsed laser lights may be applied to the locations of thefirst plurality of cells 8504. For example, an imaging subsystem of thecell culture system may identify the locations of each cell in the cellculture cavity, and identify which cells are of the first celltype/stage versus the second cell type/stage using image analysis and/ormachine learning. A computing subsystem may control a laser to targetthe locations of the first plurality of cells 8504 with pulsed lasers.The pulsed laser lights create microbubbles 8508 within the cell culturecavity. The microbubbles 8508 and their subsequent collapse may causethe first plurality of cells 8504 to be dislodged from the adheringsurface 8502. In other implementations, other methods of dislodging thefirst plurality of cells 8504 may be used, as described in detail withrespect to FIGS. 83A-83E.

In FIG. 85C, the first plurality of cells 8504 that have been dislodgedmay settle on the bottom surface of the cell culture cavity due togravity. The first plurality of cells 8504 may be rest there for aperiod of time until they re-adhere to the bottom surface.

In FIG. 85D, the cell culture cavity may undergo inversion 8510 so thatthe adhering surface 8502 with the second plurality of cells 8506 is nowon the bottom while the surface with the first plurality of cells 8504is on the top. A computing subsystem may apply pulsed lasers to thelocations of the first plurality of cells 8504 to lyse them and a fluidflow may push the resultant cell debris out of the cell culture cavity,as described in detail with respect to FIGS. 84A-84E.

In FIG. 85E, the cell culture cavity with only the second plurality ofcells 8506 on the top surface remain. The second plurality of cells 8506may undergo additional cell culturing until two or more celltypes/stages are grown. At that point, the process of separation,inversion, and removal described with respect to FIGS. 85A-85E may berepeated. This process may allow for selective separation and removal ofcertain cell types or stages during cell culturing, and may beparticularly useful for the culturing of semi-adherent cells, such asimmune cells (e.g., dendritic cells, T cells, monocytes, andmacrophages).

FIG. 86 is a flow chart illustrating a method 8600 of semi-adherent cellculturing in a cell culture system in accordance with variousimplementations. The method 8600 may be performed by a cell culturesystem (e.g., cell culture system 100 in FIG. 1 ). The method 8600 maybe similar to the process described with respect to FIGS. 85A-85E.

In block 8602, a cell culture may be developed in a cell culturecontainer (e.g., cell culture container 106). The cell culture cavity inthe cell culture container may contain cells of at least a first andsecond cell type/stage. The first and second cell types/stages mayinclude various types of immune cells, such as T cells, dendritic cells,and macrophages. The first and second cell types/stages may be differenttypes or stages of semi-adherent cells. For example, the first celltype/stage may be a dendritic cell and the second cell type/stage may bea monocyte. In another example, the first cell type/stage may be animmature dendritic cell and the second cell type/stage may be a maturedendritic cell. The cells of the first and second cell types/stages mayadhere to a top surface of the cell culture cavity, with the force ofgravity acting downwards from the top surface to the bottom surface.

In block 8604, the cell culture system may dislodge cells of the secondcell type/stage from the top surface. An imaging subsystem of the cellculture system may identify the locations of each cell in the cellculture cavity, and identify which cells are of the first celltype/stage versus the second cell type/stage. The cell culture systemmay utilize a number of methods to dislodge cells of the second celltype/stage, including using agitation tools, pulsed laser lights, andfluid flows as illustrated in FIGS. 83A-83E. The dislodged cells of thesecond cell type/stage may settle on the bottom surface of the cellculture cavity. In block 8606, the cells of the second cell type/stagemay be given time to re-adhere to the bottom surface of the cell culturecavity.

In block 8608, the cell culture system may invert the cell culturecavity. For example, the cell culture system may include one or moreactuators connected to the cell culture chamber containing the cellculture cavity that may act on the cell culture chamber to invert it.When inverted, the bottom surface containing the re-adhered cells of thesecond cell type/stage may now be the top surface and the top surfacecontaining cells of the first cell type/stage may now be the bottomsurface.

In block 8610, the cell culture system may remove the cells of the firstcell type/stage from the cell culture cavity. The cell culture systemmay utilize a number of methods to remove cells of the first celltype/stage from the bottom surface, including using collection tools,pulsed laser lights, and fluid flows as illustrated in FIGS. 84A-84E.Once removed, the method 8600 may return to block 8602 and continueculturing of the cells of the second or more cell type/stage untilmultiple cell types/stages are grown, in which case the cell culturesystem may separate the different cell types/stages and selectivelyremove some of them. In this manner, the method 8600 enables automated,controlled culturing of cells, which may be particularly useful forlarge scale derivation and manufacturing of semi-adherent cells.

For the particular application of derivation and manufacturing of immunecells, the cell culture system may enable end-to-end large-scaleproduction of immune cells from an input cell type. Starting withvirtually any input cell type, such as fibroblasts or CD34+ cells, thecell culture system may reprogram the input cells into iPSCs usingmethods described herein, and then expansion of iPSCs to usefultherapeutic doses. The iPSCs may then be directed to differentiate andeventually mature towards various cells of the myeloid lineage,including dendritic cells. During this differentiation process towards apredefined end product, the cell culture may pass through various celltypes and cell clusters of varying levels of adherence. The iterativecomputer guided, time controlled, laser-based, inversion aided processdescribed herein will enable selection throughout the differentiationand maturation process resulting in a highly functional, highly pure endproduct based on phenotypes recognized by a computer, such as thepresence or lack thereof of dendrites or adherence level. For example,early in the differentiation process, non-adherent or semi-adherentcells may be flowed from the first cell culture cavity to a second cellculture cavity and allowed to settle in the second cell culture cavityfor the next stage of differentiation. As another example, adherentcells such as macrophages for a purely dendritic cell-based product ornon-functional cells such as immature dendritic cells after the cellculture was supplemented with a maturation cocktail may be removed fromthe cell culture cavity during the differentiation process.

Selective Material Extraction and Analysis

During a cell culture process, it may be beneficial to selectivelycollect and sample cells in the cell culture to determine itscharacteristics. The characteristics may be used in differentapplications. For example, a computing subsystem (e.g., computingsubsystem 100) may associate characteristics of the sampled cells withthe cell regions or colonies that the cells came from. It may also beimportant to image live cells at multiple timepoints to enable themeasurement of trends at the subcellular, cellular, cell neighborhood,or colony level. Another application of selective cell sampling andcharacterizing is to monitor the cell culture state, for example duringa cell-based process or in a bio production system, and doing so in aselective manner in order to obtain a representative sample of cellmaterial. This may allow a cell culture system to determine whether thecell culture process should be continued, altered, or stopped based onthe attributes of the harvested cells. The information may also be usedin machine learning models to improve future cell culture processes.

The characteristics of the cells that may be observed or measured fromlabel-free images may include, but are not limited to, morphology,presence/count/size of subcellular components, density, refractiveindex, absorption or absorption spectrum, polarization-dependentabsorption or refractive index, degree of attachment to substrate orsurrounding cells, proliferation rate, velocity, projection of celloutgrowths such as neurites, interaction with other cells, andspectroscopic characteristics including but not limited to Ramanspectra, infrared spectra, autofluorescence, etc. The measured orobserved characteristics may also include parameters measurable byfluorescent labelling, such as surface markers or other components knownto the industry. The measured or observed characteristics may alsoinclude phenotypic, genomic, epigenetic, transcriptomic, proteomiccharacteristics of those cells.

The selective cell extraction and analysis should be done in situ onlive or recently live cell cultures in a cell culture vessel suitablefor long-term cell processes, and observation should be conducted viaimaging. The cell extraction process should be minimally invasive sothat the remaining cells can remain in culture and continue the cellprocess. In addition, it should be compatible with a closed orsemi-closed cell culture system such as a flask or microfluidic cellculture chamber, or other 90D cell culture vessel that does not allowmanual access to the cell culture region. The selective cell extractionand analysis should also be compatible with existing analysistechniques, including but not limited to qPCR, RNA sequencing, DNAsequencing, karyotyping, DNA methylation sequencing, chromatinaccessibility measurements such as ATACseq/MNase-seq/DNase-seq, andproteomic measurements including but not limited to microarrays, liquidchromatography, and mass spectroscopy.

There are several current approaches in the art for sampling cellsduring a cell culture process. One example is laser microdissection.This is a well-established technique by which samples are “cut out” ofcell or tissue sheets and retrieved for analysis. Often the technique isused on preserved intact tissues, or when cells have been secured to afoil for extraction. The disadvantages of this technique are that it isgenerally relevant to continuous tissues only, not where there areindividual cells, and requires mechanical extraction of the cut-out cellsheets, which is performed in a number of ways—all of which aregenerally incompatible with a long-term cell culture system,particularly one that is semi-closed (like a tissue culture flask) orentirely closed (like a microfluidic cell culture vessel).

Another approach is foil-based, in which tissue is attached to a foilwhich absorbs laser radiation and may be cut, allowing sections to becut and then retrieved mechanically. Another approach is membraneretrieval, in which after cutting of the tissue section of interest, a“stamp” that contains a textured membrane is lowered onto the tissuesurface to make contact with the section of interest and retrieve it.There is also ejection/gravity, in which a section of tissue issuspended (on a foil) in air, and sections that are laser-cut drop offinto a collection chamber. Another method is called fluorescent in-situhybridization (FISH), including both DNA-FISH and RNA-FISH. Thistechnique allows a number of pre-determined DNA sequences or RNAsequences to be labelled and imaged in situ. However, cells must befixed prior to hybridization and labelling, the number of sequences thatcan be examined is generally limited, and high-resolution fluorescencemicroscopy is required to image the fluorophores. Yet another approachis micropipette-based extraction of cells, or cellular components. Thesetechniques are able to target individual cells, or small groups ofcells, and are able to work on live cell cultures.

There are also spatial transcriptomic techniques for cell sampling.These techniques rely on a specialized surfaces that has been pre-codedwith DNA sequences to allow tracing of the spatial origin of RNAmolecules. To date these techniques have been developed primarily fortissue sections that have been preserved in a thin slice, for use inpathology or ex-vivo studies. The drawbacks of this approach are thatthey do not apply to in situ measurement of live cell cultures, and thatthey are currently restricted to RNA sequencing.

In short, while existing methods address situations where preservedtissue samples are used, or may act on recently-live cells but withexpensive instruments and consumables, there are few viable options forusing standard analytical methods in conjunction with dynamic live cellimaging. Particularly, no current approach is suitable for performingsuch measurements inside of closed or semi-closed cell culture vessels,and potentially within the course of a cell process (without damagingthe remaining live cells). Thus what is needed in the art are methods ofextracting and sampling cells during a cell culture process in a closed,automated cell culture system while not disturbing the cell growthprocess.

The systems and methods disclosed herein include a system for selectivecell extraction and sampling which is compatible with a cell culturesystem (e.g., cell culture system 100). The system may include a cellculture chamber suitable for long-term cell culture and imaging, acoating on the cell culture chamber for laser absorption (but transmitsimaging light), an imaging subsystem configured to image cells residenton the coated surface, a computing subsystem for selecting one or morecells for analysis, and a cell editing subsystem that utilizes laserpulses that strike the coating, causing an explosive microbubble andcavitation. The cells are de-adhered from the coated surface as a resultof the microbubbles and are harvested via liquid extraction, and/orcells are lysed by the microbubbles and their components are harvestedvia liquid extraction. The cells and/or cell components may then beanalyzed via a range of analytical techniques. In some implementations,the analyzed cells may be selected by their image characteristics,including time series image characteristics and/or analysis thereof. Insome implementations, a series of laser processes and liquid removalprocesses may be used to sample multiple subpopulations.

Additional methods of targeted cell extraction or cell lysis arecontemplated in this disclosure. For example, cells may be extractedusing magnetic tools operable in a live cell culture container,including a closed fluidic chamber or cassette. The magnetic tool may becontrolled by an external component actuating the in-chamber component,the external component guided by a computing subsystem based on imagingdata. In an alternate example, focused ultrasound operable in a livecell culture container, including a closed fluidic chamber or cassette,may be used to extract cells. An external transducer transmittingfocused sound waves through the container wall may be used to focus oncells of interest and loosen them from the cell culture surface. Thetransducer may be controlled by a computing subsystem based on imagingdata.

Cell lysis may take place in situ, and resulting debris are removed fromthe container with the surrounding liquid. If cell lysis is done insitu, the cell culture fluid media may be replaced with an “extractionand measurement” media prior to lysis. This extraction media may be freeof potential contaminants, components that will interfere with thedownstream measurements, or sample-degrading components such as RNAse.In some implementations when cell lysis takes place in situ, the cellsmay be fixed prior to the process, and reverse transcription of RNA tocDNA may be performed in situ. This “freezes” the state of the cellculture, preserves mRNA information, and allows for a multi-partselective harvest of material over a longer period if needed.

Cells may be selectively harvested intact through this selective method,with lysis done prior to analysis, enabling single-cell measurements.Once cells or cell debris have been selectively separated from the cellculture, harvest may be done in a number of ways, including but notlimited to, pipetting (including automated pipetting systems) for opencell culture containers such as microwell plates, and liquid replacementand outflow in closed fluidic chambers, in which the liquid exitingchamber flushes the extracted cells with it.

There may be several approaches for selecting cells for extraction. Forexample, one approach is random sampling of cells from a cell culture.This may include random area selection for cells or cell components in ahigh-confluency cell culture (e.g., choosing random 90D patches to actupon with transducer and then harvesting the material) or random areaselection from within cell-bearing areas, based on an image of the cellculture. Using such an image, regions of different local densities maybe randomly sampled to obtain a representative sample. In anotherapproach, the sampling may be guided by manual annotation of images ofthe cell culture, with humans observing the cell culture image andselecting regions of interest, and the cell editing subsystem actingupon these areas prior to sample extraction.

In another approach, the sampling may be guided by image characteristicsas measured by a computing subsystem (e.g., computing subsystem 100).The relevant image characteristics may include (1) outputs of imageprocessing subsystems that measure local density, morphology, order,orientation, etc.; (2) outputs of machine learning models whose input isthe images of the cell culture and whose output is a spatial mapclassifying the cell culture at the cell, neighborhood, region, colonyor other level (the machine learning model may be, for example, asupervised model that has been trained with labelled data or anunsupervised model that classifies spatial regions into a series ofclusters based on image data alone); (3) outputs of a computingsubsystem that locates each cell in the cell culture and computes localcharacteristics such as cell morphology, density, colony membership,etc.; and (4) outputs of a computing subsystem that locates each colonyand computes colony characteristics, including time seriescharacteristics.

FIGS. 87A-E are diagrams illustrating selective cell extraction andanalysis of adherent cells in accordance with various implementations.In FIG. 87A, cells 8702 undergo a cell culture process in a cell culturecontainer 8704. The cells 8702 may be adhered to a surface of the cellculture container 8704, the surface configured to allow imaging (e.g., atransparent surface). The cells are imaged using an imaging subsystem8706 (e.g., cell imaging subsystem 112), which transmits data to acomputing subsystem 8708 (e.g., computing subsystem 110). In oneexample, the computing subsystem 8708 may classify the regions of cellsusing an unsupervised clustering model which classifies cell regions bytexture, morphological characteristics, and time series characteristics(e.g., changes of properties over time, optical flow measurements).Similarly, the computing subsystem 8708 may identify individualcolonies, and categorize cells by colony membership.

In FIG. 87B, the computing subsystem 8708 may select a first group ofcells for lysing using any of the methods described herein (e.g.,unsupervised clustering models). The computing subsystem 8708 maycontrol a cell editing subsystem 8712 (e.g., cell editing subsystem 114)to lyse the selected cells using a non-contact lysis method. Forexample, the cell editing subsystem 8712 may be a steered pulsed lasersystem that interacts with a coating on the internal surface of the cellculture container 8704 to form explosive microbubbles and lyse thetargeted cells. Prior to this lysing process, the cell media in the cellculture container 8704 may be exchanged for a specialized, temporarylysis and material harvest buffer that is RNAse free and/or may containcompounds to accelerate cell dissociation upon lysis.

In FIG. 87C, liquid is withdrawn from the cell culture container 8704.The liquid contains the components of the cells that were targeted andlysed by the cell editing subsystem 8712. In the example shown in FIG.87C, an automated pipetting system 8714 is used to withdraw the liquidfrom the cell culture container 8704. The automated pipetting system8714 may optionally position the pipette to draw liquid from thespecific region where cells were lysed, and withdraw only a portion ofthe total liquid in the cell culture container 8704, in order tomaximize the concentration of the cellular constituents within theharvested liquid. The automated pipetting system 8714 is only onepossible method of liquid extraction. In general, multiple liquidextraction methods may also be utilized to withdraw liquid containingthe lysed cell components. The lysing and extraction process illustratedin FIGS. 87B-C may be repeated multiple times for each distinct cellpopulation that has been identified.

In FIG. 87D, extracted cell samples may be processed for analysisaccording to one or more pre-existing analysis techniques. For example,two cell samples 8702 a and 8702 b may have been extracted. In oneexample, each sample 8702 a, 8702 b is analyzed by qPCR, and levels ofexpression for a series of target genes, along with housekeeping genesthat normalize for cell quantity, are measured and compared to eachother as well as reference readings. The data analysis is represented inFIG. 87D by chart 8716. This approach may allow analysis of multiplecell phenotypes that are linked to image or image timeseriescharacteristics. This information may be used in future predictive modeland process optimization operations by a cell culture system. Forexample, a cell culture system may selectively lyse cells and removethem from the cell culture container for analysis. The cell culturesystem may utilize the resulting information to monitor progression andsuccess of similar cell cultures with imaging alone and the use of amachine learning model (now trained with the qPCR data and otherinformation), and may also use the information to optimize the cellculture process given certain output cell target attributes.

Various cellular components obtained through the extraction techniquesdisclosed herein can be used as biomarkers suitable for downstreamanalysis. Examples of cellular components include cell surface proteins(particularly surface biomarkers), cytoplasmic proteins, cytoplasmicRNA, nuclear proteins, mitochondrial DNA/RNA, nuclear DNA/RNA, andextracellular vesicles (EVs) and their associated materials (endosome,exosome, and their associated contents). RNA could include total RNA,run-on RNA transcripts, enhancer RNAs, general non-coding RNAs(including but not limited to incRNAs, lincRNAs, snoRNAs, miRNAs, andsimilar), mRNAs, or any combination thereof.

Various capture technologies can be used to obtain the target cellularcomponent(s). Bead capture can be used to capture cellular componentsafter laser cell lysis. In some cases, the primary capture method usesmagnetic beads targeting a given cellular component. Examples includeDNAs/RNAs capture using SPRI paramagnetic beads (such as AmpureXP), andantibody-conjugated protein capture superparamagnetic beads (such asprotein A/G dynabeads pre-conjugated to an antibody targeting a proteinof interest). Alternative bead/slurry methods could also be utilizedwhen appropriate, such as coated agarose-based bead capture forisolation of targeted molecules. Capture may also be achieved throughcollection of total lysed material in an appropriate buffer for furtherdownstream analysis, followed by gradient ultracentrifugation to isolatethe components of interest (in the case of EVs, for example).

The captured cellular component(s) can be analyzed according to variousavailable analytical methods. For RNAs, suitable methods include allforms of applicable NGS, including but not limited to total RNAseq,mRNAseq, scRNAseq, enhancer RNAseq, and exome capture sequencingapproaches. More targeted qPCR-based evaluations and/or arrays may beused to evaluate isolated RNAs on a smaller scale as well. For DNAs,suitable methods include all forms of applicable NGS, including but notlimited to ATACseq, ChIPseq, scATACseq, whole exome sequencing, wholegenome sequencing, or targeted DNA region or portion sequencing. Moretargeted qPCR-based evaluations and/or arrays may be used to evaluateisolated DNAs on a smaller scale as well.

For proteins, analysis may be performed using an extremely wide anddiverse array of downstream applications depending on the quantity andpurity that can be isolated. Mass-spectrometry analysis based orantibody probe based methods can be used to evaluate, for example, theidentity and/or quantity of select protein biomarkers. Alternatively,any of a vast number of other protein analytics methods could be appliedas necessary (e.g., Western Blot, ELISA, immunostaining, etc.).

Following the selective extraction of cell material, the cell cultureprocess may continue in the cell culture container 8704, as shown inFIG. 87E. Thus the implementations disclosed allows harvest of cellmaterial (often a very small fraction of the overall growth) from a livecell culture and therefore allows the remaining cells to progress to anendpoint of the cell culture process without interruption. In someimplementations, the selective harvest and analysis may be performed atmultiple points during the cell culture process. The methods disclosedherein may be used for cell processes including, but not limited to,stem cell reprogramming (e.g., iPSCs), stem cell differentiation,trans-differentiation, cell maturation, cell gene editing, clonal growthand selection, etc. The methods disclosed herein may be used for thepurpose of training image-based models for predicting cell processoutcomes, or may be used directly to select optimal regions, colonies,clones, cell cultures for further processing.

FIGS. 88A-C are diagrams illustrating selective cell extraction andanalysis of semi-adherent cells in accordance with variousimplementations. The semi-adherent cells may be grown in a cell culturecontainer having a closed liquid chamber, and the cells may be selectedfor extraction based on imaging or imaging time series characteristics.In FIG. 88A, a closed liquid chamber may include a volume of liquidmedia 8802 bounded by an upper surface 8804 and a lower surface 8806.The upper and lower surfaces may be transparent so that cells within theclosed liquid chamber may be imaged using transmitted-light imaging(e.g., brightfield imaging, Zernike phase imaging, darkfield imaging,differential interference contrast imaging, quantitative phase imaging,etc.).

In the example shown in FIG. 88A, cells 8808 have been introduced intothe closed liquid chamber when it was inverted (i.e., the upper surface8804 is below the lower surface 8806), and due to their semi-adherence,attach weakly to the upper surface 8804 when the chamber is invertedback to the orientation shown in FIG. 88A. When the closed liquidchamber is inverted to the orientation shown in FIG. 88A, any cells ordebris that are not adhered to the upper surface 8804 drop towards thelower surface 8806 and may be washed out of the closed liquid chamber bypumping liquid through it.

An imaging subsystem 8810 (e.g., cell imaging subsystem 112) may imagethe cells 8808 that are attached to the upper surface 8804 at one ormore timepoints. A computing subsystem (e.g., computing subsystem 110)may calculate characteristics of individual cells based on size,morphology, intracellular components, polarization dependence,refractive index, phase, cell division, or other characteristicscaptured by the images. In some implementations, fluorescent labels maybe applied as well to indicate presence of specific surface markers. Insome implementations, time series trends of one or more of the measuredcharacteristics are used. As a result of these observations, cells aregrouped by classifications. The cells may be grouped automatically bythe computing subsystem or manually by a human operator who can look atthe distribution of these characteristics (e.g., one or more scatterplots) and select one or more clusters of cells of interest.

A non-invasive selective cell harvesting system (e.g., cell editingsubsystem 894) may be used to dislodge selected cells 8812 with aspecific classification from the upper surface 8804, as shown in FIG.88B. For example, the cell harvesting system may be a pulsed lasersystem which creates microbubbles when it strikes an absorbing film onthe upper surface 8804. The microbubbles detach the selected cells 8812from the upper surface 8804, causing them to fall away from the uppersurface 8804 into the liquid media 8802 contained within the cellchamber.

The selected cells 8812 are then harvested from the closed liquidchamber by exchanging the liquid media 8802 in the chamber as shown inFIG. 88C. The media exchange may be done as part of a regular mediachange. The selected cells 8812 are then collected for analysis. Becausethe selected cells 8812 are intact when extracted, both bulk analysistechniques as well as single-cell techniques such as single-cell RNAseqmay be used on the harvested cells.

FIGS. 89A-C are diagrams illustrating a cell culture process withselective cell extraction and analysis in accordance with variousimplementations. FIG. 89A illustrates a perfused cell culture chamber8902 in which a cell culture 8904 is growing. For example, the cellculture 8904 may be an adherent cell culture in a continuous perfusion2D reactor and may be approaching maximum specified cell confluency. Thecell culture 8904 may be imaged periodically to assess confluency, andoptionally to locate cells/colonies for treatment. The number of cellsmay be periodically reduced via a non-invasive cell editing method (forexample, using the laser, ultrasonic or magnetic tool techniquesdescribed herein) to prevent overgrowth of cells. This may be useful forcertain cell culture processes, for example during clearing of episomalor viral vectors from cells, in which each cell division reduces theload of vectors in the cell population.

In FIG. 89B, a subset of the cells 8906 in the cell culture may betargeted for lysis. The selected subset of cells 8906 is shown as darkbands as shown in FIG. 89B. The cells may be selected in a pre-setpattern as shown in FIG. 89B, or may be based on the configuration ofcells in the cell culture 8904. For example, cells may be selected fromregions of the cell culture 8904 that are most dense, or regions thatare approaching the bounds of the cell culture chamber 8902 (whereconditions are more variable), or some combination of these or otherfactors.

The selected subset of cells 8906 may be lysed, as shown in FIG. 89C,and the lysed cells are suspended in the fluid media in the cell culturechamber 8902. The fluid media may be exchanged or flushed, and at leasta portion of the spent fluid media containing the lysed cell debris maybe collected by a sampling bag 8908 or some other collection mechanism.In the case of collection via the sampling bag 8908, a pinch valve 8910in the primary fluid path may be closed to direct the fluid media intothe sampling bag 8908. The sampling bag 8908 may be subsequentlydetached with a sterile tube welder, which enables sterile detachment ofthe sample bag 8908 from the cell culture system. The contents of thesampling bag 8908 may then be sent to analysis. In alternateimplementations, an analysis system may be directly connected to thecell culture system to allow online measurements of the resultingcellular matter without detachment of a sample bag or container. Such anonline system may perform further fractionization/homogenization of thecell debris, filtration, preparation steps and then analysis of the cellcontents.

Using the example of iPSC reprogramming in which a reprogramming vectoris cleared over time, the measurement enabled by the system may include,for example, a qPCR measurement of the contents of the sampling bag 8908to measure RNA expression levels of: (1) one or more housekeeping genes(e.g., GAPDH) in order to normalize for the cell count; (2) one or morecomponents of the reprogramming vector, for example OCT4 if the episomalreprogramming vector contained it, in order to monitor clearance of thevector; and (3) one or more non-vector gene expressions to measurepluripotency markers of the cells, for example SSEA4 if not included inthe vector. The vector-specific measurement could assess progress inclearing the vector from the cells (a necessary condition for completionof the process). The endogenous gene expression is used to verify thatthe cell culture remains highly pluripotent and is not differentiating.Optionally, regions that are potentially differentiating may beselectively harvested in a separated iteration from regions that arethought to be pluripotent, and this may be confirmed by analysis of thecell lysis product.

FIG. 90 is a flow chart illustrating a method 9000 of cell extractionand analysis in accordance with various implementations. The method 9000may be performed by a cell culture system (e.g., cell culture system 100in FIG. 1 ). In some implementations, the method 9000 may be performedby a mix of an automated cell culture system and manual effort byhumans.

In block 9002, a cell culture may be grown in a cell culture container(e.g., cell culture container 106). The cell culture may be adherent orsemi-adherent cells adhered to a cell growth surface of the cell culturechamber in the cell culture container. The cell growth surface may betransparent to enable imaging of the cell culture. The cell culturecontainer may be a closed system, such as a closed cassette.

In block 9004, the cell culture system may obtain one or more images ofthe cell culture. For example, the cell culture system may include acell imaging subsystem (e.g., cell imaging subsystem 112) that isconfigured to take one or more images of the cell cultures. In someimplementations, the images may be a time-series of images of the cellculture.

In block 9006, the cell culture system may identify one or more cells toextract from the cell culture. For example, a computing subsystem (e.g.,computing subsystem 110) may identify and select one or more cells toextract based on the collected images. The computing subsystem mayutilize one or more characteristics derived from the cell images todetermine which cells to extract. The characteristics may include directmeasurements or observations from the images as well as the output ofvarious machine learning models or other algorithms that process theimage. For example, the computing subsystem may classify the regions ofcells using an unsupervised clustering model which classifies cellregions by texture, morphological characteristics, and time seriescharacteristics (e.g., changes of properties over time, optical flowmeasurements). Similarly, the computing subsystem may identifyindividual colonies and group cells by colony membership. The computingsubsystem may then select one or more cells from each cell region orcolony so that cells having different characteristics may be extractedand sampled. In some implementations, the identification of cells may bedone manually by a person rather than by the cell culture system.

In block 9008, the cell culture system may selectively extract theidentified cells. For example, a cell editing subsystem (e.g., cellediting subsystem 114) may be used to lyse or otherwise dislodge theidentified cells from the cell growth surface of the cell culturechamber. The cell editing subsystem may utilize, for example, lasers,ultrasound, or magnetic tools among other approaches, to dislodge theidentified cells without destroying them. Before extraction, the fluidmedia in the cell culture chamber may be changed to a specialized, fluidthat accelerates cell dissociation upon lysis. The dislodged cells maythen be extracted from the cell culture chamber using a fluid mediaexchange/flush, automated pipetting system, or other means.

In block 9010, the cell culture system may analyze the extracted cells.For example, qPCR assays and other tests/assays/measurements may beconducted to determine various properties and characteristics of theextracted cells. The cell culture system may periodically repeat thesteps shown in blocks 9004-9010 to extract and sample cells at differentpoints in the cell culture process.

In block 9012, the cell culture system may adjust the cell cultureprocess based on the analysis of the extracted cells. For example, thecell culture system may determine that a sampled cell from a particularcell colony is outside the preferred cell growth parameters and thus thecell colony should be destroyed. In another example, the cell culturesystem may determine that a sampled cell from a particular cell colonymay need additional nutrients and may initiate a fluid media exchange tofreshen the media in the cell culture chamber. In general, the cellculture system may change a number of environmental or growthparameters, destroy certain cells, or take other actions based on theresults of the analysis. The cell culture system may also incorporatethe data into a machine learning model to improve future cell cultureprocesses. In this manner, the method 9000 provides a way for selectiveextraction and analysis as to benefit the operation of a cell culturesystem and to provide dynamic cell growth feedback.

Wavelength-Selective Films for Cell Culture Imaging and Control

With the industrialization of cell-based processes such as bioprocessingand cell therapies, the need for tools to manipulate cells within a cellculture has grown rapidly. High variability in cell culture processeshas driven the need for tools that can be responsive to real-time cellculture conditions, not only at the vessel level but also at the locallevel. Information about cell culture conditions may be useful formaking various cell culture process decisions, such as the addition ofmedia, reagents, buffers, or other compounds to the cell culture as awhole, or decisions to terminate a cell culture, either positively forharvest or negatively for disposal.

One preferred method for monitoring cell cultures at a local level,whether it be a region, colony, local cluster of cells, or at the singlecell level is by imaging. The imaging may be conducted either byfluorescently-labeled imaging or using label-free imaging such asbrightfield, phase contrast, darkfield or other transmission/scatteringbased techniques. These techniques, in particular the label-freetechniques, require cell culture vessels and/or inserts into thesevessels that by their construction enable high-fidelity imaging, meaningthat they transmit light with high efficiency, and without impartingdiffraction or other spatial artifacts that would interfere with thecontained imaging cell cultures.

At the same time, a range of tools for active cell culture manipulationhave been developed, intended to replace mostly open-loop cell culturecontrol (in which only vessel-level changes are applied in bulk to thecontained cells), or manual processes such as pipette scratching ofcells, or manual transfer of cell colonies from one vessel to another.These tools include tools for selective cell removal, as well as toolsfor selective intracellular delivery of compounds to cells in a cellculture. A wide range of such tools used to manipulate cells aredescribed in Stewart, Martin P. et. al., “Intracellular Delivery byMembrane Disruption: Mechanisms, Strategies, and Concepts,” Chem. Rev.118, 16, 7409-7531 (2018), which is hereby incorporated by reference inits entirety.

One known method for selective cell manipulation is using opticalenergy. For example, optical cell trapping may be used to individuallymove cells, and optoporation may be used to focus light on individualcell membranes to porate them for the purpose of compound delivery, cellcontent extraction, or cell destruction. However, cells are highlytransmissive over a wide range of wavelengths from the ultraviolet (UV)to the near infrared (NIR), meaning extremely high power and energydensities are required to accomplish these operations. The devices thatgenerate this optical energy may include lasers with very high pulseenergies (and often associated low pulse rates) and/or focusingobjectives with high numerical apertures (and therefore very limitedfields of view), resulting in very low throughputs. This has made directoptical manipulation of cells suitable mostly for research only, and notfor large-scale application in bioprocessing, gene or cell therapies, orhigh-throughput drug discovery or screening.

As a result, many efforts have been made to enhance optical energyabsorption in the proximity of target cells within cell cultures. Someapproaches include optoporation, UV killing (selective cell killing in acell culture using UV lasers), photothermal and/or photochemical(photoacid), photomechanical, photomechanical or photothermal with goldnanoparticles mixed into cells, photomechanical with gold pyramids, andphotomechanical with a metal film. However, each of these approachescomes with drawbacks that make them ineffective for incorporating intoan efficient, automated, closed cell culture system. For example,optoporation requires large power and time requirements and is notscalable; UV killing is likely to genetically alter or damage cells.Photothermal and/or photochemical (photoacid) approaches may result inchemical leaching from the film layer, high collateral damage, and slowcell death. Photomechanical approaches may cause cell death and havevery high energy and area requirements. Photomechanical or photothermalapproaches with gold nanoparticles mixed into the cells may causevariable effects across the cell culture, may alter cell health/behaviorand introduce contaminants, and may necessitate repeated dosing ofnanoparticles because cells may grow away from the nanoparticles.Photomechanical approaches with gold pyramids hinders imaging and mayalter cell culture growth and differentiation. Photomechanicalapproaches with continuous metal films introduces significant opticalloss and as a result amplifies any film defects in the cell cultureimages. Therefore, none of these approaches satisfy the requirements fora satisfactory imaging-compatible, high-throughput optical energytransfer system that does not leave exogenous compounds or particles inthe resulting cell culture. Thus there is a need for supportingcomponents that make cell imaging and editing efficient and effectivewithout comprising the underlying cell culture.

A supporting component for cell imaging and editing in cell culturesystems should ideally have several attributes and capabilities forefficient, automated cell culture imaging and editing. For example, acell culture system should be capable of delivering localized opticalenergy to a cell culture for the purpose of imparting energy to cells(for example, by causing rapid heating of cell media to form explosivemicrobubbles and cavitation, or causing highly localized heating ofcells) for the purpose of destroying specific cells, or forintracellular delivery or extraction of compounds into/from cells. Thecell culture system should have a high efficiency of conversion fromoptical energy to local thermal and/or mechanical energy, such that asignificant amount of energy is transferred within a small volume. Thisallows the use of lower-energy optical sources and/or allows very highthroughput (e.g., area and number of cells processed per unit time).

The supporting component should also be capable of imparting opticalenergy without the addition or leaching/escape of exogenous compounds orparticles into the cell culture, which may alter the behavior of thecell culture, be deleterious to the health of the cells, or leaveresidual compounds in cells to be used in downstream applications. Inaddition, the supporting component should use materials that are knownto be biocompatible and non-toxic, and have a surface that in its baseconfiguration is free of mechanical features that could perturb cellgrowth or differentiation.

The supporting component should also achieve energy absorption andconversion using an absorbing layer that, while meeting the criteriaabove, allows high-fidelity imaging of the cell culture through thissupporting component, meaning that it imparts low optical extinction(absorption and/or scattering) at desired imaging wavelengths and doesnot result in image artifacts at the desired imaging resolution. Thesupporting component should also be configured to enable energyabsorption in cell culture chambers (“consumables”) that are constructedwith materials typically used for cell culture and/or high-throughputcell screening or high-content cell imaging, such as polymers or glass.

The systems and methods disclosed herein include a supporting componentas described above embodied as a unique optically-resonant film that ispermanently attached to a cell culture chamber, or component within acell culture chamber. The resonant optical film may be designed andconfigured to simultaneously achieve high-efficiency coupling of opticalenergy into the local cell environment at wavelengths that are notdirectly harmful to cells, and allow high-fidelity transmission andfluorescence imaging of the contained cell cultures, while obviating theneed for addition of exogenous dyes, particles, or other constructs tothe cell culture to achieve energy delivery.

The resonant optical film may be located on one surface of the cellculture chamber or may be on the surface of an insert that is placedinto the cell culture chamber. The resonant optical film may beconfigured to preferentially absorb light at one wavelength range(absorption range) while maintaining high transmission at anotherwavelength range (imaging range) using a resonant optical film designthat is resonant at the laser absorption range.

In some implementations, the resonant optical film may absorb more than5%, 10%, 15%, 20%, or 30% of light at a cell processing opticalwavelength, while absorbing less than 5%, 10%, 15% or 20% of light at acell imaging optical wavelength. In some implementations, the resonantoptical film may not have inherent features with median dimensionslarger than 10%, 20%, or 50% of the cell imaging optical wavelength,with the exception of fiducial markings imparted on it. In someimplementations, the resonant optical film may be located on a wall of acell culture chamber, or may be situated on a foil in the cell culturechamber. In some implementations, the foil may be a membrane with pores.

In some implementations, the resonant optical film may be configured tohave a resonant absorption at 532 nm and/or 1064 nm. In someimplementations, the resonant optical film may be configured towithstand laser pulses of less than 25 ns of 0.05, 0.1, 0.2, or 0.4J/cm{circumflex over ( )}2 energy with less than a certain percentage ofchange in optical transmission at the cell imaging wavelength. In someimplementations, the resonant optical film may include gold nano-islandswith mean diameter less than 20, 30, 40, or 50 nm as measured along atleast one axis. The nano-islands may be permanently attached to anoptically transparent material, which may include glass, cyclic olefincopolymer, polystyrene, polycarbonate, polyethylene terephthalate orother materials suitable for cell culture.

FIG. 91 is a graph 9100 illustrating the absorption/transmissionbehavior at different wavelengths of a resonant optical firm inaccordance with various implementations. The graph 9100 shows data fromtwo different laser-absorbing semi-transparent films developed for thepurpose of transferring laser energy to a cell culture for both cellimaging and cell editing purposes. The dashed line shows the opticaltransmission of an optical film on a cell culture chamber, namely apreviously disclosed 20 nm Titanium film. This film provided sometransmission across the entire VIS/NIR band, allowing imaging of a livecell culture. However, the optical transmission of the film was only30-35%, resulting in low transmission efficiency, therefore requiringlonger exposure times and/or more intense illumination. Forepifluorescent imaging, there were 65-70% losses on both the excitationand emission paths to and from the sample, meaning a compound efficiencyof only 9-12%, again requiring long exposure times and/or more intenseillumination. The titanium optical film absorbed 532 nm nanosecondpulsed laser light and transferred energy to targeted cells viaexplosive bubble formation and collapse. A fluence of approximately 250mJ/cm² was required to lyse and remove cells.

The solid line in the graph 9100 shows a transmission spectrum of aresonant optical film on the cell culture chamber surface in accordancewith various implementations. In this instance, the resonant opticalfilm is a 4 nm layer of gold on a 170 micron thick borosilicatecoverslip sufficiently large to form the cell culture surface of a96-well SBS microwell plate, and then annealed in order to consolidatethe material into small islands that exhibit plasmonic resonance atroughly 520-540 nm.

The resulting extinction can be seen by the dip at this wavelength, atwhich the film absorbs light from a 532 nm pulsed laser. The resonantoptical film achieves cell lysis at similar laser fluences (˜250mJ/cm{circumflex over ( )}2) as the titanium film. However, thetransmission through the resonant optical film, and therefore theimaging efficiency, are superior, with virtually 100% transmission atwavelengths longer than 625 nm, meaning over 3 times as much lighttransmission for transmission-type imaging, and a roughly 10×improvement in round-trip efficiency for epifluorescent imaging. Thisefficient transmission is beneficial for long-term imaging of cellcultures, as the lower illumination power or shorterillumination/exposure times that are enabled reduce exposure of cells tolight and minimize any effects on cell metabolism or health. Inaddition, the low reflectivity of the coating (near zero at imagingwavelengths) prevents a double-pass of light through the cell culture,further reducing any of these effects. This near-full transparency atimaging wavelengths also means that alterations to the optical film donot cause changes in the images observed, assuming a band-limited lightsource (or image sensor) is used to capture a transmission image of thesample.

FIG. 92 is an image of a microwell plate 9200 with a resonant opticalfilm on the cell-bearing surface in accordance with variousimplementations. The microwell plate 9200 depicted in FIG. 92 is a96-well SBS-standard format microwell plate fitted with a resonantoptical absorbing film on the cell-facing surface. As may be seen in thebottom left wells, the coverslip and film are highly transmissive overmost wavelengths, allowing high-quality imaging. The film may have apink-ish hue due to the enhanced absorption in the green wavelengthrange.

The microwell plate 9200 is an example implementation of a cell culturechamber, but in general many cell culture chambers known in the art maybe used. For example, microwell plate 9200 is not limited to 96 wells,but may include single-well plates to 6, 12, 24, 96, 384, 1536 and othernumbers of wells on the microwell plate, as well as well plates withmicrowells within each well for the purpose of isolating cells or cellclusters. In addition, the cell culture chamber may include well plateinserts such as transwell membranes constructed with a permeable polymermembrane and coated with the resonant optical firm to allow cells to becultured on a permeable membrane between two layers of media (often withdifferent contents), and to be manipulated using optical radiation thatis absorbed by the resonant optical film for the purpose of lysis orcompound delivery.

In alternate implementations, the cell culture chamber may include petridishes, flasks, or other large cell culture chambers with resonantabsorbing films to allow for larger-format cell cultures. In such cases,the coating may be applied directly to the chamber wall(s), or it may beinserted into the cell culture chamber using a coating-bearing sheetmade of thin glass or polymer that is attached to a chamber wall.Alternate implementations of cell culture chambers may also encompassesclosed fluidic chambers in which media flows through the chamber, suchas microfluidic or macro-scale fluidic flow chambers that allowautomated media perfusion of cell cultures.

FIGS. 93A-C are images of cells undergoing cell editing and washing in acell culture chamber having a resonant optical film in accordance withvarious implementations. FIG. 93A shows human induced pluripotent stemcells (hiPSCs) grown in a region of a cell culture chamber, with alaser-absorbing resonant optical film on the cell culture chambersurface. Imaging, performed with a 10× objective, shows a high level ofdetail in the cell culture. FIG. 93B shows the same region of cellsimmediately following pulsed laser illumination with ˜40 nJ pulses, 15nsec pulse width at 532 nm, in which pulses were applied in a grid of4×4 microns over the field of view. Cell lysis is evident fromdetachment of some cells, and extensive blebbing observable along theperiphery of the cell clusters. FIG. 93C shows the same area followingwashing of cell debris from the cell culture chamber. Cells within thefield of view have been removed completely, without marking evident onthe resonant optical film. Some cells at the edges of the scanned areaare visible, where they remain attached to intact regions outside of thescanned area. Despite spots from out-of-focus dust, the surface displaysa feature-free quality that is important for highly-repeatable imagingof cell cultures, especially when these images are used for imageprocessing routines and ultimately for automated management of the cellculture in a cell culture system (e.g., cell culture system 100). Theresonant optical film is compatible with a pulsed laser system as thecell editing subsystem. In addition to the use of pulsed laser systemsto produce microbubbles for cell lysis or intracellular delivery,continuous-wave sources (whether lasers or other sources) may be used toimpart thermal energy selectively to a cell culture using the resonantoptical film.

FIG. 94 is an image of a resonant optical film surface 9400 inaccordance with various implementations, taken by a scanning electronmicroscope (SEM). The resonant optical film surface 9400 was fabricatedusing gold deposition and subsequent film annealing at approximately500° C. to form islands that exhibit plasmonic resonance at around520-540 nm. As can be seen from the image, the maximum feature size isaround 100 nm, with the median feature size closer to 25 nm. As aresult, the film has very low scattering or absorption at the desiredimaging wavelengths (roughly >600 nm) and with no visible features at10× magnification.

The resonant optical film described herein may be fabricated usingseveral approaches. The first is using thin semiconductor films. Thinsemiconductor films may work near the edge of the bandgap, where filmthickness is tuned such that one optical resonance is at the laserwavelength (where the material absorption is relatively high) and atleast one other optical resonance point at a wavelength where theinherent absorption is lower (the point at which imaging will beperformed). For example, multiple forms of silicon have absorptioncoefficients that drop rapidly over the visible wavelength range.Deposition of thin layers of silicon onto a substrate material such asglass or plastic therefore results in a transmission spectrum with peaksand valleys in the visible and NIR wavelength range where there areoptical resonances. These resonances may then be used to preferentiallyabsorb optical radiation for manipulation of cells (at shorterwavelengths) and transmit optical radiation for imaging cells (at longerwavelengths).

An example of such a resonant film may be found in Zhou, Jaiping et al.,“Si surface passivation by SiOx: H films deposited by a low-frequencyICP for solar cell applications,” Journal of Physics D Applied Physics45(30):395401 (2012), which is hereby incorporated by reference in itsentirety. The Zhou reference discloses a transmission spectrum of ahydrogenated amorphous silicon layer with transmission maxima at ˜520 nmand ˜600 nm. The optical film disclosed in Zhou may be modified for usein the present implementations, for example by using a slightly thickerlayer to achieve a resonance at the 532 nm frequency-doubled Er:YAGlaser line, and another resonance at just over 600 nm, where high powerdensity LED illuminators are readily available for transmission imaging.

FIG. 95 is a graph 9500 showing the transmission spectrum of the filmdisclosed in the Zhou reference, which has resonances at specificwavelengths and progressively higher absorption at short wavelengths.Such a resonant, partially-absorbing layer may be deposited directly ona coverslip material (borosilicate glass or polymer). It may then becapped with a dielectric layer such as silicon dioxide or siliconnitride to form a consistent index difference interface at highcontrasts (to enhance reflection) and prevent deterioration ormodification of the semiconductor layer by cell media components. In anexample implementation, a layer of amorphous silicon is deposited byplasma-enhanced chemical vapor deposition (PECVD) onto an optical-gradesheet of cyclic olefin copolymer (COC) to form a layer of approximately400 nm. This layer is then recrystallized using a Xenon flash lamp toconvert the amorphous Silicon into microcrystalline silicon, whichexhibits a lower optical absorption at over 500 nm and has a higherthermal conductivity. The deposition layer thickness is tuned such thatit results in a half-wave multiple of 532 nm (the laser wavelength)after annealing. Finally, the silicon layer is capped with a thin (10-20nm) layer of silicon dioxide to protect the silicon and provide abiocompatible surface. The resultant resonant optical film will have aresonance at 532 nm where the material has sufficient absorbance tocapture laser light and transmit this energy in the form of heat to thecell media above it. Additionally, it has other resonant transmissionpeaks where the transmission is 75% or higher at longer wavelengths, forexample 620-650 nm, which is suitable for transmission microscopy ofcell cultures.

Another approach for fabricating optical films as disclosed herein mayinclude plasmonic resonant absorbing films. One class of these filmsuseful in the present implementations is patterned conductive structureson a transparent substrate (coverslip or insert into a cell culturechamber). Metal structures with appropriate (usually high) conductivity,dimensions, and spacing can have plasmonic resonances that may couplewith specific wavelengths. Films that are useful in the presentimplementations should (a) have high uniformity and consistency in thedistribution of absorption; (b) have no residual particles or materialsin cell culture products; and (c) prevent aggregation of materials suchas nanoparticles that could become visible in cell culture imaging.Films with resonant structures that are inherently and uniformlyattached to a surface in the cell culture chamber may satisfy thesequalities. For example, gold nanostructures with dimensions on the orderof tens of nanometers have resonances in the visible spectrum fromroughly 520 nm upwards, and can be used to absorb laser wavelengthswhile transmitting wavelengths for imaging.

Patterned films for use in the present implementations may be formed ina number of ways. One set of fabrication techniques include pre-definedpatterning. One example of pre-defined patterning is photolithographicpatterning, in which a lift-off process is used in which photoresist isapplied onto the substrate, exposed using a photomask, developed, andremoved from selected areas. Metal such as gold is then deposited ontothe substrate (where exposed) or photoresist using deposition techniquesincluding, but not limited to, evaporation or sputtering. The remainingphotoresist is then removed from the substrate, along with any gold thatwas deposited on top of it. A variation of photolithographic patterningis optical interference based photolithography, in which instead of amask being used to expose photoresist, an interference pattern is usedto produce a periodic pattern.

Another example of pre-defined patterning is nano-imprinting, in which atemplate is used to pattern photoresist on the substrate, and then thephotoresist is processed as in the photolithography approach. Arepresentative technique for such patterning is given in Lopatynskyi,Andrii M. et al., “Au nanostructure arrays for plasmonic applications:annealed island films versus nanoimprint lithography,” NanoscaleResearch Letters 10:99 (2015), which is hereby incorporated by referencein its entirety. Further examples of pre-defined patterning include:e-beam lithography, in which the plasmonic features are patterned byelectron beam writing in photoresist (described in Chen, Yifeng,“Nanofabrication by electron beam lithography and its applications: Areview,” Microelectronic Engineering Vol. 135, pp. 57-72 (2015)); ionbeam lithography (described in Wat, F., et al., “Ion Beam Lithographyand Nanofabrication: A Review, Int. J. Nanoscience, Vol. 4, No. 3, pp.269-286 (2005)); colloidal mask deposition, in which self-organizingparticles such as microspheres are layered onto the substrate andtemporarily attached (for example, spheres that form a hex-packed layeron the substrate surface), and metal is then deposited onto thesubstrate only where there are gaps in these spheres (described inSanchez-Esquivel, Hector et al., “Spectral dependence of NonlinearAbsorption in Ordered Silver Metallic Nanoprism Arrays,” ScientificReports 7(1) (2017)); and self-assembled polymers or other layers(described in Segalman, Rachel A., “Patterning with block copolymer thinfilms,” Materials Science and Engineering R 38, 191-226 (2005)), whichmay be used to pattern metallic films into plasmonic resonant structureseither by applying such a structure to the substrate, depositing metal,and then removing the structure (acting as a mask for deposition, or“lift-off” mask) to yield metal structures, or by applying such astructure to a substrate with an existing metal film, using thestructure as a mask for etching the metal film, and then removing thestructure to yield a structured metal film. Each reference listed aboveare incorporated by reference in their entirety.

Another set of fabrication techniques for patterned films includeself-forming patterned metal films. In this technique, a film of metalis first deposited on the substrate (for example, a layer of gold onto aborosilicate glass), and then annealed to form semi-random islands basedon surface energy alone. While the islands are random, the distributionof island sizes and spacing is controllable and repeatable, and as aresult the optical properties of the films are consistent from spot tospot and from sample to sample. Metal is deposited by mechanismsincluding but not limited to evaporation, e-beam evaporation, andsputtering, and then annealed to form islands by one or more methods.The annealing methods may include oven annealing (in which the substrateand film are placed in an oven, for example a nominal 3 nm gold filmannealed for 8 hours at 500° C., in a nitrogen environment) and opticalannealing (in which the substrate and as-deposited film are exposed tointense light, for example laser light or intense flash lamps, in orderto heat the film and cause it to form plasmonic islands). For example,using optical annealing a 532 nm laser may be used to anneal the filmwith repeated pulses. Such optical annealing may be done in a gasenvironment, or in a liquid environment for the purpose of dissipatingheat and removing any particulates that form, and generally reflect theultimate operating environment of the plasmonic film during thispre-treatment. In alternate implementations, the islands may be createdvia direct deposition of metal onto a substrate under appropriateconditions, for example sputtering gold onto a borosilicate glass atelevated temperature. This may allow the film to re-form into islands asit is deposited, which may directly yield a plasmonic resonant film. Anexample is described in Tvarozek, V. et al., “Plasmonic behaviour ofsputtered Au nanoisland arrays,” Applied Surface Science Vol. 395, pp.241-247 (2017), which is hereby incorporated by reference in itsentirety. In some implementations, high-conductivity metals such asgold, which form the plasmonic structures, may be co-deposited withother materials such as titanium to promote adhesion to the substratematerial.

Another set of fabrication techniques for patterned films includedeposition of metallic nanoparticles and then permanent attachment to anoptically clear substrate. In this approach, pre-formed nanoparticles ina liquid are applied and attached to the substrate material, for exampleas described in Ahmed, Syed Rahin el al., “In situ self-assembly of goldnanoparticles on hydrophilic and hydrophobic substrates for influenzavirus-sensing platform,” Scientific Reports 7, 44495 (2017), which ishereby incorporated by reference in its entirety. For cell manipulationapplications (as opposed to sensing applications such as the onedescribed in Ahmed), the resonant optical film is configured to absorb asignificant amount of energy, and may need to operate over a period ofdays or weeks without detachment of constituent materials. For thatreason, both chemical and thermal methods may be used to create a strongattachment between the nanoparticles and surface. For example, thedeposition of metallic nanoparticles and permanent attachment may befollowed by a thermal annealing process in which the nanoparticlesre-shape and increase contact area with an underlying glass or polymersubstrate.

It should be understood that the disclosed implementations of resonantoptical films and methods of constructing them is not exhaustive, andthat the present implementations are not dependent on a specificimplementation. Rather, in general the present implementations utilize acombination of resonant optical films within a cell culture chamber thatachieves the goal of efficient cell culture imaging and editing within acell culture system, particularly one that is automated. The propertiesof the resonant optical film should be conductive to accurate and easyimaging.

Terms and Definitions

Unless otherwise defined, all technical terms used herein have the samemeaning as commonly understood by one of ordinary skill in the art towhich this disclosure belongs.

As used herein, the singular forms “a,” “an,” and “the” include pluralreferences unless the context clearly dictates otherwise, and encompass“at least one.” Any reference to “or” herein is intended to encompass“and/or” unless otherwise stated.

As used herein, the term “about” in some cases refers to an amount thatis approximately the stated amount.

As used herein, the term “about” refers to an amount that is near thestated amount by 10%, 5%, or 1%, including increments therein.

As used herein, the term “about” in reference to a percentage refers toan amount that is greater or less the stated percentage by 10%, 5%, or1%, including increments therein.

As used herein, the phrases “at least one”, “one or more”, and “and/or”are open-ended expressions that are both conjunctive and disjunctive inoperation. For example, each of the expressions “at least one of A, Band C”, “at least one of A, B, or C”, “one or more of A, B, and C”, “oneor more of A, B, or C” and “A, B, and/or C” means A alone, B alone, Calone, A and B together, A and C together, B and C together, or A, B andC together.

The term “flexible” as used herein refers to an object or material thatis able to be bent or compressed without cracking or breaking. The term“semi-flexible” as used herein refers to an object or material that hasa portion thereof that is able to be bent or compressed without crackingor breaking.

As used in any implementation herein, a “circuit” or “circuitry” mayinclude, for example, singly or in any combination, hardwired circuitry,programmable circuitry, state machine circuitry, and/or firmware thatstores instructions executed by programmable circuitry. An “integratedcircuit” may be a digital, analog or mixed-signal semiconductor deviceand/or microelectronic device, such as, for example, but not limited to,a semiconductor integrated circuit chip.

The term “coupled” as used herein refers to any connection, coupling,link or the like by which signals carried by one system element areimparted to the “coupled” element. Such “coupled” devices, or signalsand devices, are not necessarily directly connected to one another andmay be separated by intermediate components or devices that maymanipulate or modify such signals. Likewise, the terms “connected” or“coupled” as used herein in regard to mechanical or physical connectionsor couplings is a relative term and does not require a direct physicalconnection.

Unless otherwise stated, use of the word “substantially” may beconstrued to include a precise relationship, condition, arrangement,orientation, and/or other characteristic, and deviations thereof asunderstood by one of ordinary skill in the art, to the extent that suchdeviations do not materially affect the disclosed methods and systems.

It will be appreciated by those skilled in the art that any blockdiagrams herein represent conceptual views of illustrative circuitryembodying the principles of the disclosure. Similarly, it will beappreciated that any flow charts, flow diagrams, state transitiondiagrams, pseudocode, and the like represent various processes which maybe substantially represented in computer readable medium and so executedby a computer or processor, whether or not such computer or processor isexplicitly shown. Software modules, or simply modules which are impliedto be software, may be represented herein as any combination offlowchart elements or other elements indicating performance of processsteps and/or textual description. Such modules may be executed byhardware that is expressly or implicitly shown.

Also, various inventive concepts may be embodied as one or more methods,of which an example has been provided. The acts performed as part of themethod may be ordered in any suitable way. Accordingly, implementationsmay be constructed in which acts are performed in an order differentthan illustrated, which may include performing some acts simultaneously,even though shown as sequential acts in illustrative implementations.

While various implementations have been described and illustratedherein, those of ordinary skill in the art will readily envision avariety of other means and/or structures for performing the functionand/or obtaining the results and/or one or more of the advantagesdescribed herein, and each of such variations and/or modifications isdeemed to be within the scope of the implementations described herein.More generally, those skilled in the art will readily appreciate thatall parameters, dimensions, materials, and configurations describedherein are meant to be exemplary and that the actual parameters,dimensions, materials, and/or configurations will depend upon thespecific application or applications for which the teachings is/areused. Those skilled in the art will recognize, or be able to ascertainusing no more than routine experimentation, many equivalents to thespecific inventive implementations described herein. It is, therefore,to be understood that the foregoing implementations are presented by wayof example only and that, within the scope of the appended claims andequivalents thereto, implementations may be practiced otherwise than asspecifically described and claimed. In addition, any combination of twoor more such features, systems, aspects, articles, materials, kits,and/or methods, if such features, systems, aspects, articles, materials,kits, and/or methods are not mutually inconsistent, is included withinthe inventive scope of the present disclosure. Particularly, any elementof the disclosure and any aspect thereof may be combined, in any orderand any combination, with any other element of the disclosure and anyaspect thereof.

The above-described implementations can be implemented in any ofnumerous ways. For example, the implementations may be implemented usinghardware, software or a combination thereof. When implemented insoftware, the software code can be executed on any suitable processor orcollection of processors, whether provided in a single computer ordistributed among multiple computers.

Further, it should be appreciated that a computer may be embodied in anyof a number of forms, such as a rack-mounted computer, a desktopcomputer, a laptop computer, or a tablet computer. Additionally, acomputer may be embedded in a device not generally regarded as acomputer but with suitable processing capabilities, including a PersonalDigital Assistant (PDA), a smart phone or any other suitable portable orfixed electronic device. Also, a computer may have one or more input andoutput devices. These devices can be used, among other things, topresent a user interface. Such computers may be interconnected by one ormore networks in any suitable form, including a local area network or awide area network, such as an enterprise network, and intelligentnetwork (IN) or the Internet. Such networks may be based on any suitabletechnology and may operate according to any suitable protocol and mayinclude wireless networks, wired networks or fiber optic networks.

The various methods or processes outlined herein may be coded assoftware that is executable on one or more processors that employ anyone of a variety of operating systems or platforms. Additionally, suchsoftware may be written using any of a number of suitable programminglanguages and/or programming or scripting tools, and also may becompiled as executable machine language code or intermediate code thatis executed on a framework or virtual machine.

Implementations of the methods described herein may be implemented usinga processor and/or other programmable device. To that end, the methodsdescribed herein may be implemented on a tangible, non-transitorycomputer readable medium having instructions stored thereon that whenexecuted by one or more processors perform the methods. The computerreadable medium may include any type of tangible medium, for example,any type of disk including floppy disks, optical disks, compact diskread-only memories (CD-ROMs), compact disk rewritables (CD-RWs), andmagneto-optical disks, semiconductor devices such as read-only memories(ROMs), random access memories (RAMs) such as dynamic and static RAMs,erasable programmable read-only memories (EPROMs), electrically erasableprogrammable read-only memories (EEPROMs), flash memories, magnetic oroptical cards, or any type of media suitable for storing electronicinstructions.

The terms “program” or “software” are used herein in a generic sense torefer to any type of computer code or set of computer-executableinstructions that can be employed to program a computer or otherprocessor to implement various aspects of implementations as discussedabove. Additionally, it should be appreciated that according to oneaspect, one or more computer programs that when executed perform methodsof the present disclosure need not reside on a single computer orprocessor, but may be distributed in a modular fashion amongst a numberof different computers or processors to implement various aspects of thepresent disclosure.

Computer-executable instructions may be in many forms, such as programmodules, executed by one or more computers or other devices. Generally,program modules include routines, programs, objects, components, datastructures, etc. that perform particular tasks or implement particularabstract data types. Typically, the functionality of the program modulesmay be combined or distributed as desired in various implementations.Also, data structures may be stored in computer-readable media in anysuitable form.

Also, various inventive concepts may be embodied as one or more methods,of which an example has been provided. The acts performed as part of themethod may be ordered in any suitable way. Accordingly, implementationsmay be constructed in which acts are performed in an order differentthan illustrated, which may include performing some acts simultaneously,even though shown as sequential acts in illustrative implementations.

Computing System

Referring to FIG. 96 , a block diagram is shown depicting an exemplarymachine that includes a computer system 9600 (e.g., a processing orcomputing system) within which a set of instructions can execute forcausing a device to perform or execute any one or more of the aspectsand/or methodologies for static code scheduling of the presentdisclosure. The components in FIG. 96 are examples only and do not limitthe scope of use or functionality of any hardware, software, embeddedlogic component, or a combination of two or more such componentsimplementing particular implementations.

Computer system 9600 may include one or more processors 9601, a memory9603, and a storage 9608 that communicate with each other, and withother components, via a bus 9640. The bus 9640 may also link a display9632, one or more input devices 9633 (which may, for example, include akeypad, a keyboard, a mouse, a stylus, etc.), one or more output devices9634, one or more storage devices 9635, and various tangible storagemedia 9636. All of these elements may interface directly or via one ormore interfaces or adaptors to the bus 9640. For instance, the varioustangible storage media 9636 can interface with the bus 9640 via storagemedium interface 9626. Computer system 9600 may have any suitablephysical form, including but not limited to one or more integratedcircuits (ICs), printed circuit boards (PCBs), mobile handheld devices(such as mobile telephones or PDAs), laptop or notebook computers,distributed computer systems, computing grids, or servers.

Computer system 9600 includes one or more processor(s) 9601 (e.g.,central processing units (CPUs) or general purpose graphics processingunits (GPGPUs)) that carry out functions. Processor(s) 9601 optionallycontains a cache memory unit 9602 for temporary local storage ofinstructions, data, or computer addresses. Processor(s) 9601 areconfigured to assist in execution of computer readable instructions.Computer system 9600 may provide functionality for the componentsdepicted in FIG. 96 as a result of the processor(s) 9601 executingnon-transitory, processor-executable instructions embodied in one ormore tangible computer-readable storage media, such as memory 9603,storage 9608, storage devices 9635, and/or storage medium 9636. Thecomputer-readable media may store software that implements particularimplementations, and processor(s) 9601 may execute the software. Memory9603 may read the software from one or more other computer-readablemedia (such as mass storage device(s) 9635, 9636) or from one or moreother sources through a suitable interface, such as network interface9620. The software may cause processor(s) 9601 to carry out one or moreprocesses or one or more steps of one or more processes described orillustrated herein. Carrying out such processes or steps may includedefining data structures stored in memory 9603 and modifying the datastructures as directed by the software.

The memory 9603 may include various components (e.g., machine readablemedia) including, but not limited to, a random access memory component(e.g., RAM 9604) (e.g., static RAM (SRAM), dynamic RAM (DRAM),ferroelectric random access memory (FRAM), phase-change random accessmemory (PRAM), etc.), a read-only memory component (e.g., ROM 9605), andany combinations thereof. ROM 9605 may act to communicate data andinstructions unidirectionally to processor(s) 9601, and RAM 9604 may actto communicate data and instructions bidirectionally with processor(s)9601. ROM 9605 and RAM 9604 may include any suitable tangiblecomputer-readable media described below. In one example, a basicinput/output system 9606 (BIOS), including basic routines that help totransfer information between elements within computer system 9600, suchas during start-up, may be stored in the memory 9603.

Fixed storage 9608 is connected bidirectionally to processor(s) 9601,optionally through storage control unit 9607. Fixed storage 9608provides additional data storage capacity and may also include anysuitable tangible computer-readable media described herein. Storage 9608may be used to store operating system 9609, executable(s) 9610, data9611, applications 9612 (application programs), and the like. Storage9608 can also include an optical disk drive, a solid-state memory device(e.g., flash-based systems), or a combination of any of the above.Information in storage 9608 may, in appropriate cases, be incorporatedas virtual memory in memory 9603.

In one example, storage device(s) 9635 may be removably interfaced withcomputer system 9600 (e.g., via an external port connector (not shown))via a storage device interface 9625. Particularly, storage device(s)9635 and an associated machine-readable medium may provide non-volatileand/or volatile storage of machine-readable instructions, datastructures, program modules, and/or other data for the computer system9600. In one example, software may reside, completely or partially,within a machine-readable medium on storage device(s) 9635. In anotherexample, software may reside, completely or partially, withinprocessor(s) 9601.

Bus 9640 connects a wide variety of subsystems. Herein, reference to abus may encompass one or more digital signal lines serving a commonfunction, where appropriate. Bus 9640 may be any of several types of busstructures including, but not limited to, a memory bus, a memorycontroller, a peripheral bus, a local bus, and any combinations thereof,using any of a variety of bus architectures. As an example and not byway of limitation, such architectures include an Industry StandardArchitecture (ISA) bus, an Enhanced ISA (EISA) bus, a Micro ChannelArchitecture (MCA) bus, a Video Electronics Standards Association localbus (VLB), a Peripheral Component Interconnect (PCI) bus, a PCI-Express(PCI-X) bus, an Accelerated Graphics Port (AGP) bus, HyperTransport(HTX) bus, serial advanced technology attachment (SATA) bus, and anycombinations thereof.

Computer system 9600 may also include an input device 9633. In oneexample, a user of computer system 9600 may enter commands and/or otherinformation into computer system 9600 via input device(s) 9633. Examplesof an input device(s) 9633 include, but are not limited to, analpha-numeric input device (e.g., a keyboard), a pointing device (e.g.,a mouse or touchpad), a touchpad, a touch screen, a multi-touch screen,a joystick, a stylus, a gamepad, an audio input device (e.g., amicrophone, a voice response system, etc.), an optical scanner, a videoor still image capture device (e.g., a camera), and any combinationsthereof. In some implementations, the input device is a Kinect, LeapMotion, or the like. Input device(s) 9633 may be interfaced to bus 9640via any of a variety of input interfaces 9623 (e.g., input interface9623) including, but not limited to, serial, parallel, game port, USB,FIREWIRE, THUNDERBOLT, or any combination of the above.

In particular implementations, when computer system 9600 is connected tonetwork 9630, computer system 9600 may communicate with other devices,specifically mobile devices and enterprise systems, distributedcomputing systems, cloud storage systems, cloud computing systems, andthe like, connected to network 9630. Communications to and from computersystem 9600 may be sent through network interface 9620. For example,network interface 9620 may receive incoming communications (such asrequests or responses from other devices) in the form of one or morepackets (such as Internet Protocol (IP) packets) from network 9630, andcomputer system 9600 may store the incoming communications in memory9603 for processing. Computer system 9600 may similarly store outgoingcommunications (such as requests or responses to other devices) in theform of one or more packets in memory 9603 and communicated to network9630 from network interface 9620. Processor(s) 9601 may access thesecommunication packets stored in memory 9603 for processing.

Examples of the network interface 9620 include, but are not limited to,a network interface card, a modem, and any combination thereof. Examplesof a network 9630 or network segment 9630 include, but are not limitedto, a distributed computing system, a cloud computing system, a widearea network (WAN) (e.g., the Internet, an enterprise network), a localarea network (LAN) (e.g., a network associated with an office, abuilding, a campus or other relatively small geographic space), atelephone network, a direct connection between two computing devices, apeer-to-peer network, and any combinations thereof. A network, such asnetwork 9630, may employ a wired and/or a wireless mode ofcommunication. In general, any network topology may be used.

Information and data can be displayed through a display 9632. Examplesof a display 9632 include, but are not limited to, a cathode ray tube(CRT), a liquid crystal display (LCD), a thin film transistor liquidcrystal display (TFT-LCD), an organic liquid crystal display (OLED) suchas a passive-matrix OLED (PMOLED) or active-matrix OLED (AMOLED)display, a plasma display, and any combinations thereof. The display9632 can interface to the processor(s) 9601, memory 9603, and fixedstorage 9608, as well as other devices, such as input device(s) 9633,via the bus 9640. The display 9632 is linked to the bus 9640 via a videointerface 9622, and transport of data between the display 9632 and thebus 9640 can be controlled via the graphics control 9621. In someimplementations, the display is a video projector. In someimplementations, the display is a head-mounted display (HMD) such as aVR headset. In further implementations, suitable VR headsets include, byway of non-limiting examples, HTC Vive, Oculus Rift, Samsung Gear VR,Microsoft HoloLens, Razer OSVR, FOVE VR, Zeiss VR One, Avegant Glyph,Freefly VR headset, and the like. In still further implementations, thedisplay is a combination of devices such as those disclosed herein.

In addition to a display 9632, computer system 9600 may include one ormore other peripheral output devices 9634 including, but not limited to,an audio speaker, a printer, a storage device, and any combinationsthereof. Such peripheral output devices may be connected to the bus 9640via an output interface 9624. Examples of an output interface 9624include, but are not limited to, a serial port, a parallel connection, aUSB port, a FIREWIRE port, a THUNDERBOLT port, and any combinationsthereof.

In addition or as an alternative, computer system 9600 may providefunctionality as a result of logic hardwired or otherwise embodied in acircuit, which may operate in place of or together with software toexecute one or more processes or one or more steps of one or moreprocesses described or illustrated herein. Reference to software in thisdisclosure may encompass logic, and reference to logic may encompasssoftware. Moreover, reference to a computer-readable medium mayencompass a circuit (such as an IC) storing software for execution, acircuit embodying logic for execution, or both, where appropriate. Thepresent disclosure encompasses any suitable combination of hardware,software, or both.

Those of skill in the art will appreciate that the various illustrativelogical blocks, modules, circuits, and algorithm steps described inconnection with the implementations disclosed herein may be implementedas electronic hardware, computer software, or combinations of both. Toclearly illustrate this interchangeability of hardware and software,various illustrative components, blocks, modules, circuits, and stepshave been described above generally in terms of their functionality.

The various illustrative logical blocks, modules, and circuits describedin connection with the implementations disclosed herein may beimplemented or performed with a general purpose processor, a digitalsignal processor (DSP), an application specific integrated circuit(ASIC), a field programmable gate array (FPGA) or other programmablelogic device, discrete gate or transistor logic, discrete hardwarecomponents, or any combination thereof designed to perform the functionsdescribed herein. A general purpose processor may be a microprocessor,but in the alternative, the processor may be any conventional processor,controller, microcontroller, or state machine. A processor may also beimplemented as a combination of computing devices, e.g., a combinationof a DSP and a microprocessor, a plurality of microprocessors, one ormore microprocessors in conjunction with a DSP core, or any other suchconfiguration.

The steps of a method or algorithm described in connection with theimplementations disclosed herein may be embodied directly in hardware,in a software module executed by one or more processor(s), or in acombination of the two. A software module may reside in RAM memory,flash memory, ROM memory, EPROM memory, EEPROM memory, registers, harddisk, a removable disk, a CD-ROM, or any other form of storage mediumknown in the art. An exemplary storage medium is coupled to theprocessor such the processor can read information from, and writeinformation to, the storage medium. In the alternative, the storagemedium may be integral to the processor. The processor and the storagemedium may reside in an ASIC. The ASIC may reside in a user terminal. Inthe alternative, the processor and the storage medium may reside asdiscrete components in a user terminal.

In accordance with the description herein, suitable computing devicesinclude, by way of non-limiting examples, server computers, desktopcomputers, laptop computers, notebook computers, sub-notebook computers,netbook computers, netpad computers, set-top computers, media streamingdevices, handheld computers, Internet appliances, mobile smartphones,tablet computers, personal digital assistants, video game consoles, andvehicles. Those of skill in the art will also recognize that selecttelevisions, video players, and digital music players with optionalcomputer network connectivity are suitable for use in the systemdescribed herein. Suitable tablet computers, in various implementations,include those with booklet, slate, and convertible configurations, knownto those of skill in the art.

In some implementations, the computing device includes an operatingsystem configured to perform executable instructions. The operatingsystem is, for example, software, including programs and data, whichmanages the device's hardware and provides services for execution ofapplications. Those of skill in the art will recognize that suitableserver operating systems include, by way of non-limiting examples,FreeBSD, OpenBSD, NetBSD®, Linux, Apple® Mac OS X Server®, Oracle®Solaris®, Windows Server®, and Novell® NetWare®. Those of skill in theart will recognize that suitable personal computer operating systemsinclude, by way of non-limiting examples, Microsoft® Windows®, Apple®Mac OS X®, UNIX®, and UNIX-like operating systems such as GNU/Linux®. Insome implementations, the operating system is provided by cloudcomputing. Those of skill in the art will also recognize that suitablemobile smartphone operating systems include, by way of non-limitingexamples, Nokia® Symbian® OS, Apple® iOS®, Research In Motion®BlackBerry OS®, Google® Android®, Microsoft® Windows Phone® OS,Microsoft® Windows Mobile® OS, Linux®, and Palm® WebOS®. Those of skillin the art will also recognize that suitable media streaming deviceoperating systems include, by way of non-limiting examples, Apple TV®,Roku®, Boxee®, Google TV®, Google Chromecast®, Amazon Fire®, andSamsung® HomeSync®. Those of skill in the art will also recognize thatsuitable video game console operating systems include, by way ofnon-limiting examples, Sony® PS3®, Sony® PS4®, Microsoft® Xbox 360®,Microsoft Xbox One, Nintendo® Wii®, Nintendo® Wii U®, and Ouya®.

Non-Transitory Computer Readable Storage Medium

In some implementations, the platforms, systems, media, and methodsdisclosed herein include one or more non-transitory computer readablestorage media encoded with a program including instructions executableby the operating system of an optionally networked computing device. Infurther implementations, a computer readable storage medium is atangible component of a computing device. In still furtherimplementations, a computer readable storage medium is optionallyremovable from a computing device. In some implementations, a computerreadable storage medium includes, by way of non-limiting examples,CD-ROMs, DVDs, flash memory devices, solid state memory, magnetic diskdrives, magnetic tape drives, optical disk drives, distributed computingsystems including cloud computing systems and services, and the like. Insome cases, the program and instructions are permanently, substantiallypermanently, semi-permanently, or non-transitorily encoded on the media.

Computer Program

In some implementations, the platforms, systems, media, and methodsdisclosed herein include at least one computer program, or use of thesame. A computer program includes a sequence of instructions, executableby one or more processor(s) of the computing device's CPU, written toperform a specified task. Computer readable instructions may beimplemented as program modules, such as functions, objects, ApplicationProgramming Interfaces (APIs), computing data structures, and the like,that perform particular tasks or implement particular abstract datatypes. In light of the disclosure provided herein, those of skill in theart will recognize that a computer program may be written in variousversions of various languages.

The functionality of the computer readable instructions may be combinedor distributed as desired in various environments. In someimplementations, a computer program comprises one sequence ofinstructions. In some implementations, a computer program comprises aplurality of sequences of instructions. In some implementations, acomputer program is provided from one location. In otherimplementations, a computer program is provided from a plurality oflocations. In various implementations, a computer program includes oneor more software modules. In various implementations, a computer programincludes, in part or in whole, one or more web applications, one or moremobile applications, one or more standalone applications, one or moreweb browser plug-ins, extensions, add-ins, or add-ons, or combinationsthereof.

Software Modules

In some implementations, the platforms, systems, media, and methodsdisclosed herein include software, server, and/or database modules, oruse of the same. In view of the disclosure provided herein, softwaremodules are created by techniques known to those of skill in the artusing machines, software, and languages known to the art. The softwaremodules disclosed herein are implemented in a multitude of ways. Invarious implementations, a software module comprises a file, a sectionof code, a programming object, a programming structure, or combinationsthereof. In further various implementations, a software module comprisesa plurality of files, a plurality of sections of code, a plurality ofprogramming objects, a plurality of programming structures, orcombinations thereof. In various implementations, the one or moresoftware modules comprise, by way of non-limiting examples, a webapplication, a mobile application, and a standalone application. In someimplementations, software modules are in one computer program orapplication. In other implementations, software modules are in more thanone computer program or application. In some implementations, softwaremodules are hosted on one machine. In other implementations, softwaremodules are hosted on more than one machine. In further implementations,software modules are hosted on a distributed computing platform such asa cloud computing platform. In some implementations, software modulesare hosted on one or more machines in one location. In otherimplementations, software modules are hosted on one or more machines inmore than one location.

Databases

In some implementations, the platforms, systems, media, and methodsdisclosed herein include one or more databases, or use of the same. Inview of the disclosure provided herein, those of skill in the art willrecognize that many databases are suitable for storage and retrieval ofimage data, cell types, attribute categories, labels, assay data, or anycombination thereof. In various implementations, suitable databasesinclude, by way of non-limiting examples, relational databases,non-relational databases, object oriented databases, object databases,entity-relationship model databases, associative databases, and XMLdatabases. Further non-limiting examples include SQL, PostgreSQL, MySQL,Oracle, DB2, and Sybase. In some implementations, a database isinternet-based. In further implementations, a database is web-based. Instill further implementations, a database is cloud computing-based. In aparticular implementation, a database is a distributed database. Inother implementations, a database is based on one or more local computerstorage devices.

Numbered Implementations

The following implementations recite nonlimiting permutations ofcombinations of features disclosed herein. Other permutations ofcombinations of features are also contemplated. In particular, each ofthese numbered implementations is contemplated as depending from orrelating to every previous or subsequent numbered implementation,independent of their order as listed. 1. A cell culture system,comprising: a cell culture container comprising a cell culture, the cellculture receiving input cells; a cell imaging subsystem configured toacquire images of the cell culture; a computing subsystem configured toperform a cell culture process on the cell culture according to theimages acquired by the cell imaging subsystem; and a cell editingsubsystem configured to edit the cell culture to produce output cellproducts according to the cell culture process. 2. The cell culturesystem of implementation 1, further comprising at least one sensorconfigured to acquire sensor data, wherein the computing subsystem isfurther configured to perform the cell culture process according to thesensor data. 3. The cell culture system of implementation 1 or 2,further comprising at least one control component configured to affectenvironmental or physical aspects of the cell culture system, whereinthe computing subsystem is further configured to control the at leastone control component. 4. The cell culture system of any one ofimplementations 1-3, wherein the computing subsystem is furtherconfigured to perform input cell assays on the input cells. 5. The cellculture system of any one of implementations 1-4, wherein the computingsubsystem is further configured to perform output cell product assays onthe output cell products. 6. The cell culture system of any one ofimplementations 1-5, wherein the cell imaging subsystem comprises: alight source that illuminates the cell culture; a sensor configured todetect a plurality of light signals; and a multi-focus mechanismdisposed between the cell culture surface and the sensor configured togenerate the plurality of light signals from light reflected by the cellculture, wherein the plurality of light signals are representative ofcell location and structure data in three dimensions; wherein the cellculture container and the imaging subsystem are configured to moverelative to each other along a direction of movement. 7. The cellculture system of implementation 6, wherein the multi-focus mechanismcomprises tilting the sensor along the direction of movement. 8. Thecell culture system of implementation 6 or 7, wherein the multi-focusmechanism comprises a plurality of beam splitters that splits thereflected light into a plurality of paths; and the sensor comprises aplurality of detector arrays, each detector array located in a differentone of the plurality of paths and located a different distance away fromeach beam splitter. 9. The cell culture system of any one ofimplementations 6-8, wherein the multi-focus mechanism comprises adiffractive element that diffracts the reflected light into theplurality of light signals, each light signal representing data at adifferent height relative to the cell culture. 10. The cell culturesystem of any one of implementations 6-9, wherein the cell imagingsubsystem further comprises focus enhancing module configured to providevisual cues for adjusting a focus of the cell imaging subsystem system.11. The cell culture system of any one of implementations 1-5, whereinthe cell imaging subsystem comprises: a multi-wavelength light sourceilluminating the cell culture, wherein different wavelengths of lightilluminate the cell culture at different angles; a wavelength separationunit that separates light exiting the cell culture into separate lightsignals, each associated with a different wavelength band; one or moredetectors configured to detect the separate light signals and outputdetector signals; and a processing unit that receives the detectorsignals and is configured to form a representation of the cell culturefrom the detector signals. 12. The cell culture system of implementation11, wherein the cell culture is divided into a plurality of linearregions and imaging subsystem images each linear region sequentially.13. The cell culture system of implementation 11 or 12, wherein the cellimaging subsystem is continuously translated relative to the cellculture. 14. The cell culture system of any one of implementations11-13, wherein the cell imaging subsystem further comprises an autofocussystem. 15. The cell culture system of any one of implementations 11-14,wherein the cell imaging subsystem further comprises a registrationsystem. 16. The cell culture system of any one of implementations 11-15,wherein the cell culture comprises induced pluripotent stem cells. 17.The cell culture system of any one of implementations 11-16, wherein thecell culture is located in a closed cassette having transparent cellchamber walls. 18. The cell culture system of any one of implementations1-5, wherein said imaging subsystem is configured for imaging andscanning and comprises: at least one light source illuminating a cellculture sample having cells grown on a growth plane of the cell culture;an objective capturing light from the at least one light source passingthrough the cell culture sample, wherein the objective is tilted at anangle with respect to a perpendicular axis of the growth plane: and oneor more sensors to measure the light from the objective; wherein thecell culture sample is moved relative to the imaging and scanning systemsuch that the imaging system generates images at multiple heights alongthe perpendicular axis of the growth plane. 19. The cell culture systemof implementation 18, wherein the cell imaging subsystem comprises amulti-focus mechanism disposed between a cell culture surface and theone or more sensors, wherein the one or more sensors are configured togenerate a plurality of light signals from light reflected by the cellculture and captured by the objective, wherein the plurality of lightsignals are representative of cell location and structure data in threedimensions. 20. The cell culture system of implementation 18 or 19,wherein the at least one light source comprises a multi-wavelength lightsource illuminating the cell culture sample, wherein differentwavelengths of light illuminate the cell culture sample at differentangles. 21. The cell culture system of any one of implementations 18-20,wherein the cell imaging subsystem comprises a wavelength separationunit that separates light exiting the cell culture into separate lightsignals, each associated with a different wavelength band. 22. The cellculture system of implementation 21, wherein the cell imaging subsystemcomprises one or more detectors configured to detect the separate lightsignals and output detector signals. 23. The cell culture system ofimplementation 22, wherein the cell imaging subsystem comprises aprocessing unit that receives the detector signals and is configured toform a representation of the cell culture from the detector signals. 24.The cell culture system of any one of implementations 18-23, wherein thecell imaging subsystem comprises: a laser pulse generated by a lasersource and incident on the cell culture sample; and an acousto-opticdeflector/modular to adjust an incident angle of the laser pulserelative to the perpendicular axis of the growth plane; wherein the cellculture sample is moved relative to the cell imaging subsystem such thatthe laser pulse is capable of focusing on any part of the growth plane.25. The cell culture system of any one of implementations 1-24, whereinthe cell culture container comprises: a cell culture chamber having afirst surface, a second surface, and an interior between the firstsurface and the second surface; one or more cells in an interior of thecell culture chamber and adhered to the first surface; a magnetic toolin the interior of the cell culture chamber and resting on at least oneof the first surface or the second surface; a magnetic component on theexterior of the cell culture chamber and resting on at least one of thefirst surface or the second surface, the magnetic component magneticallycoupled to the magnetic tool; and an actuator removably coupled to themagnetic component and configured to move the magnetic component in oneor more directions, wherein moving the magnetic component also moves themagnetic tool in the same manner. 26. The cell culture system ofimplementation 25, wherein the actuator is further configured to rotatethe magnetic component. 27. The cell culture system of implementation26, wherein the rotation mixes fluid media inside the cell culturechamber. 28. The cell culture system of any one of implementations25-27, wherein the actuator is configured to translate the magneticcomponent around the first surface or the second surface. 29. The cellculture system of any one of implementations 25-28, wherein the magnetictool is configured to push debris in the interior of the cell culturechamber and rest on the first surface or the second surface when themagnetic component is translated around the first surface or the secondsurface. 30. The cell culture system of any one of implementations25-29, wherein the cell culture container further comprises an imagingobjective configured to determine a position of the magnetic tool. 31.The cell culture system of implementation 30, wherein the computingsubsystem is configured to control the actuator based on the position ofthe magnetic tool. 32. The cell culture system of any one ofimplementations 25-31, wherein the magnetic tool is configured to lyseor destroy one or more cells. 33. The cell culture system of any one ofimplementations 25-32, wherein the magnetic tool comprises: a permanentmagnet; a blade comprising a tip, a high-angle edge, and a low-angleedge. 34. The cell culture system of implementation 33, wherein the tipand/or the high-angle edge is used to lyse or destroy the one or morecells. 35. The cell culture system of implementation 33, wherein thelow-angle edge is used to lift the one or more cells from the firstsurface. 36. The cell culture system of any one of implementations25-35, wherein the magnetic tool comprises a permanent magnet and acircular blade. 37. The cell culture system of any one ofimplementations 25-35, wherein the magnetic tool has a length andcomprises: a permanent magnet; a sharp tip on a first end of the length;and a flexible scoop on a second end of the length. 38. The cell culturesystem of any one of implementations 1-37, wherein the cell editingsubsystem is configured to manipulate the magnetic tool. 39. The cellculture system of any one of implementations 38, wherein the cellediting subsystem comprises the actuator that is configured to move themagnetic component in one or more directions. 40. The cell culturesystem of any one of implementations 1-39, wherein the cell editingsubsystem comprises an ultrasound subsystem configured to selectivelylyse cells using targeted ultrasound. 41. The cell culture system of anyone of implementations 1-39, wherein: the cell culture containercomprises a cell culture chamber having a first surface and one or morecells in an interior of the cell culture chamber and adhered to thefirst surface; the cell imaging subsystem is configured to capture oneor more images of the one or more cells; the computing subsystem isconfigured to classify cells, cell regions, or cell colonies from theone or more images; the cell editing subsystem comprises an ultrasoundsubsystem that acts through the first surface to selectively lyse cellsaccording to the classifications provided by the computing subsystem;and a mechanism to remove material generated from cell lysis. 42. Thecell culture system of implementation 41, wherein the ultrasoundsubsystem comprises a focused ultrasound subsystem. 43. The cell culturesystem of implementation 41, wherein the ultrasound subsystem comprisesa phased-array ultrasound subsystem. 44. The cell culture system of anyone of implementations 40-43, wherein the ultrasound subsystem and theimaging subsystem are combined as a single head that translate acrossthe first surface. 45. The cell culture system of any one ofimplementations 1-44, wherein the cell culture container comprises acell culture chamber comprising: fluid media between a first wall and asecond wall, wherein the second wall is flexible; a cell cultureadherent or semi-adherent on the inside of the first wall; and a firstactuator configured to push against the second wall to create aconstricted region in the cell culture chamber; and a mechanism tocreate a high velocity flow through the constricted region, causingdislodging of cells or cell debris from the first wall. 46. The cellculture system of implementation 45, wherein the mechanism comprises apump that pumps the fluid media through the constricted region. 47. Thecell culture system of implementation 45 or 46, wherein the cell culturechamber is sealed and the mechanism comprises a second actuator thatpushes against the second wall to force the fluid media through theconstricted region. 48. The cell culture system of any one ofimplementations 1-44, wherein the cell culture container comprises acell culture chamber comprising: fluid media between a first wall and asecond wall, wherein the second wall is flexible; a cell cultureadherent or semi-adherent on the inside of the first wall; and at leastone acoustic transducer configured to apply acoustic waves to the cellculture chamber, causing dislodging of cells or cell debris from thefirst wall. 49. The cell culture system of implementation 48, whereinthe at least one acoustic transducer is located on the outside of thecell culture chamber proximate to the first wall and applies theacoustic towards the first wall in a direction perpendicular to a planeof the first wall. 50. The cell culture system of implementation 49,wherein the at least one acoustic transducer comprises two acoustictransducers coupled to the outside of the first wall and configured tocreate local distortions perpendicular to the plane of the first wallusing the acoustic waves. 51. A method of using the cell culture systemof any one of implementations 1-50, comprising: providing the cellculture container comprising the cell culture, the cell culturereceiving input cells; acquiring, with the cell imaging subsystem,images of the cell culture; performing, with the computing subsystem,the cell culture process on the cell culture according to the imagesacquired by the cell imaging subsystem; and editing, with the cellediting subsystem, the cell culture to produce output cell productsaccording to the cell culture process. 52. A method of controlling acell culture system such as that of any one of implementations 1-50,comprising: receiving, at a plurality of points of time, a plurality ofimages of a cell culture; identifying one or more cell colonies from theplurality of images; tracking the one or more cell colonies through theplurality of points of time; predicting an outcome of the one or morecell colonies; and editing the cell culture based on the predictedoutcomes of the one or more cell colonies. 53. A method of controlling acell culture system such as that of any one of implementations 1-50,comprising: receiving, at a plurality of points of time, a plurality ofimages of a cell culture; identifying a plurality of cells from theplurality of images; identifying one or more cell colonies from theplurality of cells; tracking the one or more cell colonies through theplurality of points of time; predicting an outcome of the one or morecell colonies; and editing the cell culture based on the predictedoutcomes of the one or more cell colonies. 54. The method ofimplementation 52 or 53, the method further comprising preprocessing theplurality of images. 55. The method of implementation 54, whereinpreprocessing the plurality of images comprises: normalizing theplurality of images; and stitching the plurality of images into a singlestitched image of the cell culture. 56. The method of any one ofimplementations 52-55, wherein predicting the outcome of the one or morecell colonies comprises generating an outcome score for each of the oneor more cell colonies, the outcome score representing a likelihood thatthe cell colony will generate an output cell product. 57. The method ofany one of implementations 52-56, wherein editing the cell culturecomprises removing one or more cells or one or more cell colonies fromthe cell culture. 58. The method of any one of implementations 52-57,59. A method of classifying image data in a cell culture system such asthat of any one of implementations 1-50, comprising: growing one or morecell cultures of a first cell type; obtaining image data of the one ormore cell cultures; generating, by an unsupervised learning engine, aplurality of visual categories for the first cell type from the imagedata; associating, by the unsupervised learning engine, the plurality ofvisual categories with a plurality of attribute categories; andlabeling, by an unsupervised inference engine, the image data with theplurality of attribute categories. 60. The method of implementation 59,wherein the image data is label-free. 61. The method of claim 59 or 60,further comprising: acquiring assay data from the one or more cellcultures; and utilizing the assay data to associate the plurality ofvisual categories with a plurality of attribute categories. 62. Themethod of any one of implementations 59-61, further comprising:obtaining labeled image data of the one or more cell cultures; andutilizing the labeled image data to associate the plurality of visualcategories with a plurality of attribute categories. 63. A methodproducing cells in a cell culture system such as that of any one ofimplementations 1-50, comprising: growing one or more cell cultures of afirst cell type; obtaining image data of the one or more cell cultures;generating, by an unsupervised inference engine, one or more attributemaps from the image data, wherein each attribute map comprises an imageof a cell culture annotated with cell attributes; determining one ormore actions based on the one or more attribute maps. 64. The method ofimplementation 63, wherein the cell attributes are associated withvisual categories identifiable in the image data. 65. The method ofimplementation 63 or 64, wherein the one or more actions comprise lysingselect cells in the one or more cell cultures, collecting assays onselect cells in the one or more cell cultures, or changing parameters ofcell growth of the one or more cell cultures. 66. A modular cell culturesystem comprising: a supporting structure; a plurality of processmodules in the supporting structure, each process module comprising aplurality of connectors and configured to removably host a cell culturecassette; and a computing subsystem configured to monitor a status ofeach of the plurality of process modules and each cell culture cassette.67. The modular cell culture system of implementation 66, wherein thesupporting structure is a rack. 68. The modular cell culture system ofimplementation 66 or 67, wherein the supporting structure comprises atleast one of the cell imaging subsystem, the cell editing subsystem, anda temperature control subsystem. 69. The modular cell culture system ofany one of implementations 66-68, wherein the computing subsystemgenerates a digital file for each process module and cell culturecassette, the digital file comprising the current status of theassociated component. 70. The modular cell culture system of any one ofimplementations 66-69, wherein when components are moved around themodular cell culture system, the associated digital file is also movedto ensure continuity of operations. 71. The modular cell culture systemof any one of implementations 66-69, wherein when components are movedaround the modular cell culture system, the associated digital file isalso moved or modified to indicate the movement or location of thecomponents in order to ensure continuity of operations. 72. The modularcell culture system of any one of implementations 66-71, wherein each ofthe plurality of process modules are configured to engage and disengagewith a cell culture cassette quickly and without engaging anddisengaging each of the plurality of connectors individually. 73. Themodular cell culture system of any one of implementations 66-72, whereinthe modular cell culture system comprises the cell culture system of anyone of implementations 1-50. 74. The modular cell culture system ofimplementation 73, wherein the cell culture cassette comprises the cellculture container comprising the cell culture. 75. The modular cellculture system of implementation 73 or 74, wherein the cell imagingsubsystem is configured to acquire images of one or more cells in eachcell culture cassette. 76. The modular cell culture system of any one ofimplementations 73-75, wherein the computing subsystem is configured tomonitor a status of each of the plurality of process modules and eachcell culture cassette based at least on images of one or more cells ineach cell culture cassette. 77. The modular cell culture system of anyone of implementations 73-76, wherein the computing subsystem isconfigured to perform the cell culture process on each cell culturecassette based on the status of each of the plurality of process modulesand each cell culture cassette. 78. The modular cell culture system ofany one of implementations 73-77, wherein the cell editing subsystem isconfigured to edit the one or more cells in the cell culture cassette inorder to produce output cell products according to the cell cultureprocess. 79. A cell culture system such as that of any one ofimplementations 1-50 or 66-78, comprising: a cell culture container, thecell culture containing comprising a cell culture cavity with a firstplurality of cells and a second plurality of cells, wherein: the firstplurality of cells are of a first type/stage and at least semi-adherentto a top surface of the cell culture cavity; and the second plurality ofcells are of a second type/stage and at least semi-adherent to the topsurface of the cell culture cavity; a processor configured to: determinea location of each of the first plurality of cells and second pluralityof cells; dislodge the second plurality of cells from the top surface,wherein the second plurality of cells re-adhere to a bottom surface ofthe cell culture cavity; invert the cell culture cavity; and remove thefirst plurality of cells from the cell culture cavity. 80. The cellculture system of implementation 79, wherein dislodging the secondplurality of cells from the top surface comprises at least one of: usingan agitation tool to create local forces acting on the second pluralityof cells; generating a fluid flow that creates local forces acting onthe second plurality of cells; and utilizing pulsed lasers to createlocal forces acting on the second plurality of cells. 81. The cellculture system of implementation 79 or 80, wherein removing the firstplurality of cells from the cell culture cavity comprises at least oneof: using a collection tool to push the first plurality of cells out ofthe cell culture cavity; generating a fluid flow to push the firstplurality of cells out of the cell culture cavity; and utilizing pulsedlasers to lyse the first plurality of cells. 82. The cell culture systemof any one of implementations 79-81, wherein inverting the cell culturecavity comprises turning the cell culture cavity such that the topsurface and the bottom surface are reversed. 83. The cell culture systemof any one of implementations 79-82, wherein the first and secondplurality of cells are immune cells. 84. The cell culture system ofimplementation 83, wherein the immune cells include cells derived frommyeloid or lymphoid lineages. 85. The cell culture system of any one ofimplementations 1-50 or 66-84, wherein the cell editing subsystem isconfigured for dislodging a subset of cells from a surface of a cellculture chamber of the cell culture container. 86. The cell culturesystem of implementation 85, further comprising a mechanism to removethe subset of cells from the cell culture chamber for analysis. 87. Acell culture system, comprising: a cell culture chamber having a firstsurface; one or more cells in an interior of the cell culture chamberand adhered to the first surface; an imaging subsystem configured tocollect images of the one or more cells; a computing subsystemconfigured to select a subset of cells for analysis based on the images;a cell editing subsystem for dislodging the subset of cells from thefirst surface; a mechanism to remove the subset of cells from the cellculture chamber for analysis. 88. A method of cell extraction andanalysis in a cell culture system such as that of any one ofimplementations 1-50 or 66-87, comprising: growing a cell culture in acell culture container; obtaining one or more images of the cellculture; identifying one or more cells to extract from the cell culturebased on the one or more images; extracting the identified cells fromthe cell culture chamber; and analyzing the extracted cells. 89. Themethod of implementation 88, further comprising adjusting a cell cultureprocess for the cell culture based on the analysis. 90. The method ofimplementation 89, wherein the steps of growing, obtaining, extracting,and analyzing is performed by an automated cell culture system. 91. Themethod of any one of implementations 88-90, wherein the step ofidentifying is performed by a person. 92. A cell culture chamber,comprising: a cell bearing surface; a plurality of cells grown on thecell bearing surface; and a resonant optical film located on the cellbearing surface. 93. The cell culture chamber of implementation 92,wherein the resonant optical film absorbs more than 5% of incident lightat a cell editing optical wavelength. 94. The cell culture chamber ofimplementation 92 or 93, wherein the resonant optical film absorbs lessthan 20% of incident light at a cell imaging optical wavelength. 95. Thecell culture chamber of any one of implementations 92-94, wherein theresonant optical film has physical features smaller than 50% of the cellimaging optical wavelength. 96. The cell culture chamber of any one ofimplementations 92-95, wherein there is a foil between the resonantoptical film and the cell bearing surface. 97. The cell culture chamberof implementation 96, wherein the foil is a membrane with pores. 98. Thecell culture chamber of any one of implementations 92-97, wherein theresonant optical film has a resonant absorption peak at 532 nanometers(nm) and/or 1064 nm. 99. The cell culture chamber of any one ofimplementations 92-98, wherein the resonant optical film comprises goldnano-islands attached to an optically transparent material selected fromthe following: glass, cyclic olefin copolymer, polystyrene,polycarbonate, polyethylene terephthalate. 100. The cell culture chamberof implementation 99, wherein the gold nano-islands have a mean diameterless than 50 nm along at least one axis. 101. The cell culture system ofany one of implementations 1-50 or 66-87, wherein the cell culturecontainer comprises the cell culture chamber of any one ofimplementations 92-100. 102. A cassette system for cell cultureprocessing, comprising: a) one or more cell culture chambers, each cellculture chamber configured to: i) provide a growth environment foradherent cell cultures: and ii) allow imaging of the adherent cellcultures grown in the cell culture chamber; and b) a liquid systemcoupled to the one or more cell culture chambers, wherein the liquidsystem is configured to: i) provide input fluid media to the one or morecell culture chambers; and ii) receive output fluid media from the oneor more cell culture chambers; wherein the liquid system is configuredto provide a closed, sterile liquid environment for the adherent cellcultures in each cell culture chamber. 103. The cassette system ofimplementation 102, wherein at least one of the input fluid media andthe output fluid media comprises at least one of growth media, reagents,buffers, fluid waste, and cell collection media. 104. The cassettesystem of implementation 103, wherein the liquid system comprises one ormore reservoirs for holding different types of fluid media. 105. Thecassette system of implementation 102, wherein the cassette systemfurther comprises at least one pump for directing the input fluid media,the output fluid media, or both through the liquid system. 106. Thecassette system of implementation 105, wherein the at least one pump isbidirectional. 107. The cassette system of implementation 102, whereineach cell culture chamber comprises a first semi-transparent surface toallow for imaging of the adherent cell cultures. 108. The cassettesystem of implementation 107, wherein each cell culture chamber isfurther configured to allow removal of cells from the cell culturechamber using a cell editing mechanism. 109. The cassette system ofimplementation 108, wherein the cell editing mechanism is configured todirect laser energy, ultrasound, or mechanical forces upon the cellculture chamber to effectuate removal of cells. 110. The cassette systemof implementation 109, wherein the laser energy comprises pulsed laserlight. 111. The cassette system of implementation 109, wherein the firstsemi-transparent surface comprises a coating configured to absorb thelaser energy at one or more wavelengths and convert the laser energyinto thermal or mechanical energy to remove cells. 112. The cassettesystem of implementation 102, wherein at least one of the one or morecell culture chambers has a cell growth area of at least 50 cm². 113.The cassette system of implementation 102, wherein at least one of theone or more cell culture chambers is completely filled with fluid media.114. The cassette system of implementation 102, wherein an internalheight of at least one of the one or more cell culture chambers is lessthan 1 millimeter. 115. The cassette system of implementation 102,further comprising: a) one or more sensors; and b) a processorconfigured to communicate with the one or more sensors and a processmodule hosting the cassette system via a pluggable connector. 116. Thecassette system of implementation 115, wherein the cassette system isremovably coupled to the process module. 117. The cassette ofimplementation 116, wherein the cassette system is configured forinsertion into the process module in a first orientation, a second,inverted orientation, or both. 118. The cassette system ofimplementation 115, wherein the one or more sensors comprise atemperature sensor, a humidity sensor, a gas-phase oxygen concentrationsensor, a gas-phase carbon dioxide concentration sensor, a dissolvedoxygen concentration sensor, a dissolved carbon dioxide concentrationsensor, a gas flow rate sensor, a liquid flow rate sensor, a pH sensor,an optical absorption sensor, an optical scattering sensor, a massspectroscopic sensor, a viscosity sensor, or any combination thereof.119. The cassette system of implementation 102, wherein each cellculture chamber comprises a gas-permeable surface. 120. The cassettesystem of implementation 102, wherein the liquid system provides theinput fluid media, receives the output fluid media, or both, via aone-time aseptic connector, a one-time aseptic disconnector, a reusablenon-aseptic connector, or any combination thereof. 121. The cassettesystem of implementation 102, further comprising a mixing and exchangesection configured to: a) mix a circulated fluid comprising the inputfluid, the output fluid, or both; b) control a concentration of adissolved gas in the circulated fluid; or c) control a temperature ofthe one or more cell culture chambers. 122. The cassette system ofimplementation 121, wherein the mixing and exchange section comprises aliquid feedback mechanism, a gas exchange mechanism, or both. 123. Thecassette system of implementation 102, further comprising a sensingsection configured to monitor a condition of the input fluid media, theoutput fluid media, or both. 124. The cassette system of implementation102, wherein the liquid system is configured to provide the input mediato each cell culture chamber at a velocity flow that applies acontinuous or directional shear stress of less than about 10 dyne/cm² tothe adherent cell culture. 125. The cassette system of implementation102, wherein each adherent cell culture chamber comprises a registrationmark, and wherein the imaging of the adherent cell cultures captures animage of the registration mark. 126. The cassette system ofimplementation 102, wherein the cassette system comprises a single-useportion and a permanent portion comprising a reusable housing enclosingthe single-use portion, wherein the single-use portion comprises the oneor more cell culture chambers and the liquid system. 127. The cassettesystem of implementation 126, wherein the single-use portion comprisesone or more bags or chambers for holding media reagents, waste products,or cellular products. 128. The cassette system of implementation 102,wherein: a) the input fluid media is provided to the one or more cellculture chambers via a first valve; b) the output fluid media isreceived from the one or more cell culture chambers via a second valve;or c) both. 129. The cassette system of implementation 102, whereinimaging the cell cultures comprises transmission imaging, reflectionimaging, brightfield imaging, darkfield imaging, phase imaging,differential interference contrast (DIC) imaging, quantitative phaseimaging (QPI), transmission Fourier ptychographic imaging, reflectiontransmission Fourier ptychographic imaging, holographic imaging, or anycombination thereof. 130. A cell culture system, comprising: a) a cellculture chamber having a first surface, a second surface, and aninterior between the first surface and the second surface; b) aplurality of cells in the interior of the cell culture chamber andadhered to the first surface; c) a magnetic tool in the interior of thecell culture chamber; d) a magnetic component located exterior to thecell culture chamber, the magnetic component magnetically coupled to themagnetic tool; and e) an actuator removably coupled to the magneticcomponent and configured to move the magnetic component in one or moredirections, wherein moving the magnetic component also moves themagnetic tool in the same manner. 131. The cassette system ofimplementation 130 wherein the actuator is configured to translateand/or rotate the magnetic component, thereby translating and/orrotating the magnetic tool. 132. The cell culture system ofimplementation 131, wherein the translation and/or rotation of themagnetic tool inside the cell culture chamber agitates fluid mediainside the cell culture chamber. 133. The cell culture system ofimplementation 132, wherein the agitation dislodges cells, cellcomponents, or cell products from the first surface and/or moves cells,cell components, or cell products floating in the fluid media around thecell culture chamber. 134. The cell culture system of implementation131, wherein the magnetic tool makes physical contact with one or morecells in the plurality of cells to dislodge them from the first surface.135. The cassette system of implementation 130 further comprising animaging subsystem configured to capture images of the plurality ofcells. 136. The cell culture system of implementation 135, furthercomprising a computing subsystem configured to: a) identify one or morecells in the plurality of cells for removal based on the images; and b)control the actuator to move the magnetic tool to remove the one or morecells. 137. The cell culture system of implementation 136, wherein theimaging system is further configured to capture images of the magnetictool. 138. The cell culture system of implementation 136, wherein thecomputing subsystem identifies the one or more cells using a machinelearning algorithm. 139. The cell culture system of implementation 136,wherein the computing subsystem is further configured to control avelocity, an orientation, a path, or any combination thereof of theactuator. 140. The cell culture system of implementation 136, whereinthe computing subsystem is further configured to control a magnetic polealignment of the actuator. 141. The cell culture system ofimplementation 136, wherein the computing subsystem is furtherconfigured to: a) engage the actuator with the first surface of the cellculture chamber; b) engage the actuator with the second surface of thecell culture chamber; c) disengage the actuator with the first surfaceof the cell culture chamber; d) disengage the actuator with the secondsurface of the cell culture chamber; or e) any combination thereof. 142.The cassette system of implementation 130 further comprising a cellculture container enclosing the cell culture chamber, wherein the cellculture container controls fluid media into and out of the cell culturechamber in a closed loop, sterile environment. 143. The cell culturesystem of implementation 142, wherein the cell culture containerencloses a plurality of cell culture chambers. 144. The cassette systemof implementation 130 wherein the magnetic tool contacts the firstsurface and the magnetic component rests on the exterior of the firstsurface. 145. The cassette system of implementation 130 wherein themagnetic tool contacts the second surface and the magnetic componentrests on the exterior of the second surface. 146. The cassette system ofimplementation 130 wherein at least a portion of the magnetic tooland/or magnetic component is coated with a polymer. 147. The cellculture system of implementation 146, wherein the polymer is configuredto make a surface of the magnetic tool and/or magnetic component thatcontacts the cell culture chamber inert, biocompatible, non-stick,non-scratching, or any combination thereof. 148. The cassette system ofimplementation 130 wherein the cell culture chamber has a growth area ofat least about 50 cm². 149. The cassette system of implementation 130wherein the cell culture chamber has a chamber height of less than about3 mm. 150. The cassette system of implementation 130 wherein themagnetic tool further comprises a blade configured to lift one or moreof the plurality of cells from the first surface, the second surface, orboth. 151. The cell culture system of implementation 150, wherein theblade comprises a low angle edge configured for non-destructiveincremental lifting of one or more of the plurality of cells. 152. Thecell culture system of implementation 150, wherein the blade comprises ahigh angle edge configured to lyse and/or destroy one or more of theplurality of cells. 153. The cassette system of implementation 130wherein at least a portion of the magnetic tool is flexible. 154. Amodular bioprocessing system, comprising: a) one or more processmodules, each process module configured to manage and monitor a cellculture process; b) a server rack, wherein the one or more processmodules are removably located on the server rack: and c) one or moreshared subsystems on the server rack and supporting the one or moreprocess systems. 155. The modular bioprocessing system of implementation154, wherein each process module is configured to removably couple to acell culture cassette hosting the cell cultures via one or morepluggable connectors. 156. The modular bioprocessing system ofimplementation 154, wherein the cell culture process is carried outwithin a cell culture container comprising a closed cassette system, amicro plate, a flask, a cell culture vessel, a microfluidic chamber, orany combination thereof. 157. The modular bioprocessing system ofimplementation 156, further comprising a transport mechanism configuredto transport the cell culture container between locations within theserver rack. 158. The modular bioprocessing system of implementation157, wherein the transport mechanism comprises a rail, a linearactuator, a motor, a bearing, a wheel, or any combination thereof. 159.The modular bioprocessing system of implementation 157, wherein thetransport mechanism is configured to provide horizontal and/or verticaltransportation of the cell culture container. 160. The modularbioprocessing system of implementation 156, wherein the closed cassettesystem comprises at least one transparent or semi-transparent surfacethat allows for light or laser-based imaging and editing. 161. Themodular bioprocessing system of implementation 156, further comprising afront-facing instrument panel configured to receive and/or eject theclosed cassette system, the micro plate, the flask, the cell culturevessel, the microfluidic chamber, or any combination thereof. 162. Themodular bioprocessing system of implementation 154, wherein the one ormore shared subsystems comprise at least one of a computing subsystem, adata storage subsystem, an environmental control subsystem, a lasersource subsystem, and a gas distribution subsystem. 163. The modularbioprocessing system of implementation 154, wherein the one or moreprocess modules comprises at least one of a cell imaging subsystem, acell editing subsystem, and a temperature control subsystem. 164. Themodular bioprocessing system of implementation 163, wherein the cellimaging subsystem comprises a brightfield imaging system, a phaseimaging system, a quantitative phase imaging system, a transmissivedarkfield imaging system, a reflective darkfield, imaging system, afluorescent imaging system, or any combination thereof. 165. The modularbioprocessing system of implementation 163, wherein the cell imagingsubsystem is configured to capture images of the cell culture process.166. The modular bioprocessing system of implementation 165, wherein theone or more shared subsystems comprises a computing subsystem configuredto perform a machine learning function to monitor the cell cultureprocess based on the images. 167. The modular bioprocessing system ofimplementation 163, wherein the cell editing subsystem is configured toselectively remove one or more cells from the cell culture process. 168.The modular bioprocessing system of implementation 154, wherein theserver rack has one or more standardized computer server rack sizes.169. The modular bioprocessing system of implementation 154, furthercomprising a backup power module for providing uninterrupted power tothe one or more process modules and the one or more shared subsystems.170. The modular bioprocessing system of implementation 154, furthercomprising a temperature control subsystem configured to manage atemperature of at least one of the cell culture process and a reagent.171. The modular bioprocessing system of implementation 154, furthercomprising a pH control subsystem configured to manage a pH of the cellculture process. 172. The modular bioprocessing system of implementation154, further comprising a gas content control subsystem configured tomanage a dissolved oxygen and/or carbon dioxide content of at least oneof the cell culture process and a reagent. 173. The modularbioprocessing system of implementation 154, further comprising a mediacontrol subsystem configured to provide and/or extract a media from atleast one of the one or more process modules. 174. The modularbioprocessing system of implementation 154, wherein the cell cultureprocess comprises cell reprogramming, cell differentiation, cell geneediting, cell incubation, cell expansion, cell sorting or purification,cell-based bioproduction, or any combination thereof 175. The modularbioprocessing system of implementation 154, wherein the modularbioprocessing system has a multi-rack configuration comprising aplurality of the server rack. 176. An imaging system, comprising: a) atleast one light source illuminating a sample; b) an objective capturinglight from the at least one light source passing through the sample; andc) one or more sensors to measure the light captured by the objective,wherein the sample moves continuously relative to the at least one lightsource and the objective during the measurement; and d) a computingsubsystem configured to generate quantitative phase images of the samplebased on the measurements from the one or more sensors. 177. The imagingsystem of implementation 176, wherein the movement of the samplerelative to the at least one light source and the objective during themeasurement generates image data at multiple focal planes along an axisperpendicular to a horizontal plane of the sample and the quantitativephase images are generated from the image data at multiple focal planes.178. The imaging system of implementation 177, wherein the objective istilted at an angle with respect to the axis. 179. The imaging system ofimplementation 176, wherein the movement of the sample relative to theat least one light source and the objective during the measurementgenerates image data at multiple illumination angles relative to thesample and the quantitative phase images are generated from the imagedata at multiple illumination angles. 180. The imaging system ofimplementation 179, wherein the at least one light source emits light atmultiple wavelengths and different wavelengths illuminate the sample atdifferent angles. 181. The imaging system of implementation 176, furthercomprising a laser source configured to manipulate the sample based onthe quantitative phase images. 182. The imaging system of implementation181, wherein the sample is moved continuously relative to the lasersource. 183. The imaging system of implementation 181, wherein the lasersource and the one or more light sources share the objective. 184. Theimaging system of implementation 181, wherein the sample is a cellculture sample and the laser source is configured to edit the cellculture sample. 185. The imaging system of implementation 184, whereinthe cell culture sample is enclosed in a cell culture chamber, the cellculture chamber comprising at least one transparent or semi-transparentsurface. 186. The imaging system of implementation 185, wherein the cellculture chamber comprises a transparent upper window and a transparentlower window. 187. The imaging system of implementation 185, wherein thecell culture chamber comprises at least one semi-transparent coating onthe at least one transparent surface configured to absorb laserradiation and direct absorbed energy to one or more cells in the cellculture chamber. 188. The imaging system of implementation 187, furthercomprising a film within the cell culture chamber, wherein the filmcomprises a fiducial marker and wherein the fiducial marker is patternedin the laser absorbing film. 189. The imaging system of implementation181, wherein the laser source is configured to generate a laser having awavelength of about 500 nm to about 600 nm or about 1000 nm to about1100. 190. The imaging system of implementation 181, wherein the lasersource is configured to generate a laser having a pulse rate of at leastabout 100 kHz. 191. The imaging system of implementation 181, furthercomprising a laser autofocus system configured to: a) project a laserfrom the laser source onto the cell culture; b) move the sample relativeto the laser source; c) repeat steps a) and b); d) measure a sharpnessof the laser based on the light captured by the objective lens duringsteps a)-c); and e) focus the laser based on the measured sharpness.192. The imaging system of implementation 176, wherein the sensorcomprises a CMOS sensor, a CCD sensor, or both. 193. The imaging systemof implementation 176, wherein the sensor comprises an array of sensorsin one or more directions. 194. The imaging system of implementation176, wherein the computing subsystem is configured to compute structuralinformation on individual cells, groups of cells, or regions or coloniesusing the quantitative phase images of the sample. 195. The imagingsystem of implementation 176, wherein the computing subsystem isconfigured to apply machine learning to analyze the measurements fromthe one or more samples. 196. The imaging system of implementation 195,wherein the computing subsystem is configured to use a convolutionalneural network to reconstruct sample amplitude and phase. 197. Theimaging system of implementation 195, wherein the computing subsystem isconfigured to use a convolutional neural network to reconstruct sampleamplitude and phase or determine one or more cell quality features. 198.The imaging system of implementation 176, comprising a first lightsource and a second light source, wherein the first light source and thesecond light source emit light at different wavelengths. 199. A methodfor generating quantitative phase images of a sample, comprising: a)illuminating a sample using at least one light source; b) capturing,with an objective, light from the at least one light source passingthrough the sample; and c) measuring, with one or more sensors, thelight captured by the objective, wherein the sample moves continuouslyrelative to the at least one light source and the objective during themeasurement; and d) generating, with a computing subsystem, quantitativephase images of the sample based on the measurements from the one ormore sensors. 200. A monoclonal induced pluripotent stem cell (iPSC)product made by the process comprising: a) placing input cells in a cellculture chamber of a closed cell culture container; b) reprogramming atleast a portion of the input cells into a plurality of clonal iPSCcandidate cells; c) collecting imaging data on a plurality of clonaliPSC candidate cell colonies emerging from the plurality of clonal iPSCcandidate cells; d) selecting one of the plurality of clonal iPSCcandidates cell colonies for expansion based on the imaging data; e)removing non-selected clonal iPSC candidate cell colonies using a cellediting mechanism; and f) expanding the selected clonal iPSC candidatecell colony into the monoclonal iPSC product. 201. The monoclonal iPSCproduct of implementation 200, wherein the imaging data comprises atime-series images of the plurality of clonal iPSC candidate cellcolonies. 202. The monoclonal iPSC product of implementation 200,wherein selecting one of the plurality of clonal iPSC candidates cellcolonies for expansion comprises: a) applying a predictive model to theimage data to predict clonal quality and functionality of each of theplurality of clonal iPSC candidate cell colonies; and b) selecting oneof the plurality of clonal iPSC candidates cell colonies based on thepredicted clonal quality and functionality of each of the plurality ofclonal iPSC candidate cell colonies. 203. The monoclonal iPSC product ofimplementation 202, wherein the predictive model is trained on priorclonal cell colony data and clonal iPSC product quality andfunctionality assays. 204. The monoclonal iPSC product of implementation202, wherein the clonal quality and functionality are determined bybased on one or more phenotypic features. 205. The monoclonal iPSCproduct of implementation 204, wherein the one or more phenotypicfeatures comprise a cell morphology, a cell proliferation rate, achromatin condensation, a nucleus to cytosol ratio, a cell migrationpattern, or any combination thereof. 206. The monoclonal iPSC product ofimplementation 200, the process further comprising: removing contaminantcells in proximity to the plurality of clonal iPSC candidate cellcolonies using the cell editing mechanism. 207. The monoclonal iPSCproduct of implementation 200, wherein the closed cell culture containerfurther comprises a sterile-sealed liquid system for providing fluidmedia to the cell culture chamber and receiving fluid media from thecell culture chamber. 208. The monoclonal iPSC product of implementation200, wherein the cell editing mechanism comprises laser radiation. 209.The monoclonal iPSC product of implementation 200, wherein a surface ofthe cell culture chamber is laser-absorbant. 210. The monoclonal iPSCproduct of implementation 200, wherein the cell editing mechanismcomprises a magnetic tool in the cell culture chamber and actuated fromoutside the cell culture chamber. 211. The iPSC product ofimplementation 210, wherein the magnetic tool comprises a rare-earthmagnet. 212. The monoclonal iPSC product of implementation 200, whereinthe cell editing mechanism comprises focused ultrasound waves. 213. Themonoclonal iPSC product of implementation 200, wherein the cell editingmechanism comprises directed energy projected from outside the cellculture chamber. 214. The monoclonal iPSC product of implementation 200,wherein the closed cell culture container comprises a single closed cellculture container. 215. The monoclonal iPSC product of implementation200, wherein the one or more of the input cells comprise a B lymphocytescell, a blood-derived epithelial cell, a C lymphocytes cell, a cardiacmuscle cell, a chondrocyte cell, an endothelial cell, an epidermal cell,an epithelial cell, an erythrocyte cell, a fibroblast cell, a granulosaepithelial cell, a hair follicle cell, a hematopoietic cell, ahepatocyte cell, a keratinocyte cell, a macrophage cell, a melanocytecell, a monocyte cell, a mononuclear cell, a neuron cell, a pancreaticislet cell, a sertoli cell, a somatic cells, a urine-derived epithelialcell, or any combination thereof. 216. The monoclonal iPSC product ofimplementation 200, wherein the reprogramming is performed using genomeintegration, non-genome integration, minicircle vectors, the Sendaiprotocol, mRNA, self-replicating RNA, CRISPR activators, recombinantproteins, or any combination thereof. 217. The monoclonal iPSC productof implementation 216, wherein the monoclonal iPSC product istransgene-free. 218. The monoclonal iPSC product of implementation 200,wherein the monoclonal iPSC product is suitable for differentiation intoa target cell type. 219. The monoclonal iPSC product of implementation200, wherein the non-selected clonal iPSC candidate cell colonies aredetermined based on at least a cell division time, a cell highreprogramming cargo load, a cell migration characteristic, a cell speed,a cell trackability, or any combination thereof. 220. The monoclonaliPSC product of implementation 200, wherein the process is performedwithin a cassette system providing a closed, sterile environment forcell culture processing. 221. The monoclonal iPSC product ofimplementation 200, wherein the process is performed within a modularbioprocessing system configured to produce a plurality of monoclonaliPSC products corresponding to different subjects. 222. A method forproducing a monoclonal induced pluripotent stem cell (iPSC) product,comprising: a) placing input cells in a cell culture chamber of a closedcell culture container; b) reprogramming at least a portion of the inputcells into a plurality of clonal iPSC candidate cells; c) collectingimaging data on a plurality of clonal iPSC candidate cell coloniesemerging from the plurality of clonal iPSC candidate cells; d) selectingone of the plurality of clonal iPSC candidates cell colonies forexpansion based on the imaging data; e) removing non-selected clonaliPSC candidate cell colonies using a cell editing mechanism; and f)expanding the selected clonal iPSC candidate cell colony into themonoclonal iPSC product.

What is claimed is:
 1. An imaging system, comprising: (a) a light sourceconfigured to illuminate a cell culture sample, wherein the cell culturesample comprises one or more cells that are adherent to a surface of thecell culture chamber; (b) an objective configured to capture light fromthe light source passing through the cell culture sample; (c) a sensorconfigured to acquire a plurality of images based on the captured light;(d) an actuator coupled to the cell culture chamber or the objective,wherein the actuator is configured to perform continuous movement of (i)the cell culture chamber relative to the light source and the objectiveor (ii) the light source and the objective relative to the cell culturechamber, wherein the continuous movement is performed during acquisitionof each of the plurality of images ; and (e) a computer processorprogrammed to generate quantitative phase images of the cell culturesample based at least in part on the acquired plurality of images . 2.The imaging system of claim 1, wherein the continuous movement allowsthe plurality of images to be acquired at each of a plurality ofdifferent focal planes along an axis perpendicular to a horizontal planeof the cell culture sample.
 3. The imaging system of claim 2, whereinthe objective is tilted at an angle with respect to the axis.
 4. Theimaging system of claim 1, wherein the continuous movement allows theplurality of images to be acquired at each of a plurality of differentillumination angles relative to the cell culture sample.
 5. The imagingsystem of claim 4, wherein the light source emits light at a pluralityof different wavelengths, and wherein the plurality of differentwavelengths illuminates the cell culture sample at a plurality ofdifferent angles.
 6. The imaging system of claim 1, further comprising alaser source configured to manipulate the cell culture sample based atleast in part on the quantitative phase images.
 7. The imaging system ofclaim 6, wherein the cell culture chamber further undergoes continuousmovement relative to the laser source, or the laser source furtherundergoes continuous movement relative to the cell culture chamber. 8.The imaging system of claim 6, wherein the objective is shared by thelaser source and the light source.
 9. The imaging system of claim 6,wherein the laser source is further configured to edit the cell culturesample.
 10. The imaging system of claim 9, wherein the cell culturesample is enclosed in the cell culture chamber, and wherein the cellculture chamber comprises a transparent or semi-transparent surface. 11.The imaging system of claim 10, wherein the cell culture chamber furthercomprises a transparent upper window and a transparent lower window. 12.The imaging system of claim 10, wherein the cell culture chamber furthercomprises a semi-transparent coating on the transparent surfaceconfigured to absorb laser radiation and direct absorbed energy to oneor more cells in the cell culture chamber.
 13. The imaging system ofclaim 12, further comprising a film within the cell culture chamber,wherein the film comprises a fiducial marker patterned thereon.
 14. Theimaging system of claim 6, wherein the laser source is furtherconfigured to generate a laser having a wavelength of about 500nanometers (nm) to about 600 nm, or about 1000 nm to about 1100 nm. 15.The imaging system of claim 6, wherein the laser source is furtherconfigured to generate a laser having a pulse rate of at least about 100kilohertz (kHz).
 16. The imaging system of claim 1, further comprising alaser autofocus system configured to: (i) project a laser from a lasersource onto the cell culture sample; (ii) move the cell culture samplerelative to the laser source, or move the laser source relative to thecell culture sample; (iii) measure a sharpness of the laser based atleast in part on light captured by the objective during operations (i)and (ii); and (iv) focus the laser based at least in part on themeasured sharpness of the laser.
 17. The imaging system of claim 1,wherein the sensor comprises a complementary metal-oxide semiconductor(CMOS) sensor, a charge-coupled device (CCD) sensor, or a combinationthereof.
 18. The imaging system of claim 1, wherein the sensor comprisesan array of sensors oriented in one or more directions.
 19. The imagingsystem of claim 1, wherein the computer processor is further programmedto determine structural information of individual cells, groups ofcells, regions of cells, or colonies of cells, based at least in part onthe quantitative phase images of the cell culture sample.
 20. Theimaging system of claim 1, wherein the computer processor is furtherprogrammed to perform a machine learning analysis of the acquiredplurality of images or the quantitative phase images.
 21. The imagingsystem of claim 20, wherein the machine learning analysis furthercomprises using a convolutional neural network to reconstruct amplitudeand phase information of the cell culture sample.
 22. The imaging systemof claim 20, wherein the machine learning analysis further comprisesusing a convolutional neural network to determine one or more featuresindicative of a cell quality of the cell culture sample.
 23. The imagingsystem of claim 1, wherein the light source further comprises a firstlight source and a second light source, wherein the first light sourceand the second light source emit light at different wavelengths.
 24. Amethod for generating quantitative phase images of a cell culturesample, comprising: (a) illuminating a cell culture sample using a lightsource, wherein the cell culture sample comprises one or more cells thatare adherent to a surface of the cell culture chamber; (b) capturing,with an objective, light from the light source passing through the cellculture sample; (c) acquiring, with a sensor, a plurality of imagesbased on the captured light; (d) performing, during acquisition of eachof the plurality of images, continuous movement of (i) the cell culturechamber relative to the light source and the objective or (ii) the lightsource and the objective relative to the cell culture chamber; and (e)generating, with a computer processor, quantitative phase images of thecell culture sample based at least in part on the acquired plurality ofimages.
 25. The imaging system of claim 20, wherein the computerprocessor is further programmed to determine features indicative of acell culture state, a cell quality, or a cell phenotype of one or morecells of the cell culture sample, based at least in part on the machinelearning analysis.
 26. The imaging system of claim 25, wherein the cellculture state comprises an assessment of cell growth within a designatedgrowth area or beyond the designated growth area.
 27. The imaging systemof claim 25, wherein the cell quality comprises an assessment of denseor sparse cell growth, cell morphology, cell division rate, cellmotility, or any combination thereof.
 28. The imaging system of claim25, wherein the cell phenotype comprises an induced pluripotent stemcell (iPSC) phenotype, a non-iPSC phenotype, a spontaneouslydifferentiated phenotype, or a non-spontaneously differentiatedphenotype.
 29. The imaging system of claim 19, wherein the structuralinformation comprises a location, a density, a nuclear location, anintracellular structure, a 3-dimensional (3-D) profile, a refractiveindex, or a combination thereof.
 30. The imaging system of claim 1,wherein the cell culture sample comprises induced pluripotent stem cells(iPSCs).
 31. The imaging system of claim 1, wherein the actuator iscoupled to the cell culture chamber, and wherein the actuator isconfigured to perform continuous movement of the cell culture chamberrelative to the light source and the objective.
 32. The imaging systemof claim 1, wherein the actuator is coupled to the objective, andwherein the actuator is configured to perform continuous movement of thelight source and the objective relative to the cell culture chamber. 33.The method of claim 24, wherein (d) further comprises performing, duringthe acquisition of each of the plurality of images, continuous movementof the cell culture chamber relative to the light source and theobjective.
 34. The method of claim 24, wherein (d) further comprisesperforming, during the acquisition of each of the plurality of images,continuous movement of the light source and the objective relative tothe cell culture chamber.